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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Xin Su Guifu Zhang Minxue Zhang Baoliu Ye Hongyan Xing College of IOT Engineering Hohai University Changzhou Jiangsu China Information Department Hohai University Nanjing Jiangsu China Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and Technology Nanjing China Jiangsu Key Laboratory of Meteorological Detection and Information Processing Nanjing University of Information Science and Technology Nanjing China

The rapid development of intelligent devices and wireless communication has greatly promoted the intelligence of the maritime Internet of Things (MIoT) in recent years, and the marine meteorological sensor network (MMSN) is an essential part of MIoT, providing accurate meteorological data for MIoT services. However, the frequent information interaction between the device and the external world also causes information leakage risks for MMSN. Intrusion detection technology based on deep learning is an effective defensive mechanism. Thus, we propose a lightweight one-dimensional convolutional neural network (LCNN) intrusion detection model to adapt to the MMSN environment characteristics and device heterogeneity. In addition, an improved supervised adversarial autoencoder (ISAAE) is proposed for synthesizing samples to address the problem that minority class attack samples are difficult to collect and detect. Finally, the simulation experimental results on the NSL-KDD dataset verify the effectiveness of the proposed method.

关键词： Training Wireless communication Adaptation models Convolution Computational modeling Simulation Intrusion detection

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Distributed Sea Clutter Denoising Algorithm Based on Variational Mode Decomposition

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Instrumentation 2020年第3期7卷 23-32页

作者： SUN Jiang XING Hongyan WU Jiajia Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and TechnologyNanjing 210044 Jiangsu Key Laboratory of Meteorological Detection and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044

In order to improve the detection accuracy of chaotic small signal prediction models under the background of sea clutter,a distributed sea clutter denoising algorithm is proposed,on the basis of variational modal decomposition(VMD).The sea clutter signal is decomposed into variational modal functions(VMF)with different center bandwidths by means of *** analyzing the autocorrelation characteristics of the deco mposed signal,we perform instantaneous half-period(IHP)and wavelet threshold denoising processing on the high-frequency and low-frequency components respectively,and regain the sea clutter *** on LSSVM sea clutter prediction model,this research compares and analyzes the denoising effects of *** ment results show that,the RMSE after denoising is reduced by two orders of magnitude,approximating 0.00034,with an apparently better denoising effect,compared with the root mean square error(RMSE)of the prediction before denoising.

关键词： Sea Clutter Variational Modal Decomposition Autocorrelation Properties Instantaneous Half-Period

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High-security three-dimensional CAP modulation technique integrating end-to-end constellation optimization and four-level masking

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Chinese Optics Letters 2025年第3期 13-18页

作者：张俊涛刘博任建新毛雅亚吴翔宇 Rahat Ullah 崔杰马一澜赵建业徐董董陈帅东周书宇 Institute of Optics and Electronics Nanjing University of Information Science&Technology Jiangsu Key Laboratory for Optoelectronic Detection of Atmoand Sphere and Ocean Nanjing University of Information Science&Technology Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science&Technology Institute of Electronics and Information Sun Yat-sen University

In this paper,a high-security three-dimensional carrierless amplitude and phase (3D-CAP) modulation technique is proposed,integrating deep learning with four-level *** 3D constellation geometry is optimized using an autoencoder(AE) with an additive white Gaussian noise (AWGN) channel model,reducing complexity by 40%compared to a variational autoencoder (VAE).Experimental validation on a 2 km seven-core fiber intensity modulation/direct detection (IM/DD) system shows a 1 d B improvement in receiver sensitivity.A 3D chaotic oscillator model is used for chaotic selective mapping,polynomial-like masking,constellation rotation,and subcarrier *** encrypted 3D-CAP signal achieves a key space of up to 10103,with strong anti-noise and confidentiality performance.

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Phase unwrapping by a multi-level grid method for moiré fringes

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Chinese Optics Letters 2025年第2期 36-42页

作者：陈云云何成兴程伟昊解文卓 School of Physics and Optoelectronic Engineering Nanjing University of Information Science & Technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET) Nanjing University of Information Science & Technology Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean Nanjing University of Information Science & Technology Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology

Phase unwrapping is a crucial process in the field of optical measurement, and the effectiveness of unwrapping directly affects the accuracy of final results. This study proposes a multi-level grid method that can efficiently achieve phase unwrapping. First, the phase image of the package to be processed is divided into small grids, and each grid is unwrapped in multiple directions. Then, a level-by-level coarse-graining mesh method is employed to eliminate the new data “faults”generated from the previous level of grid processing. Finally, the true phase results are obtained by iterating to the coarsest grid through the unwrapping process. In order to verify the effectiveness and superiority of the proposed method, a numerical simulation is first applied. Further, three typical flow fields are selected for experiments, and the results are compared with flood-fill and multi-grid methods for accuracy and efficiency. The proposed method obtains true phase information in just 0.5 s; moreover, it offers more flexibility in threshold selection compared to the flood-fill and region-growing *** summary, the proposed method can solve the phase unwrapping problems for moiré fringes, which could provide possibilities for the intelligent development of moiré deflection tomography.

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Rotated 8QAM probabilistic shaping scheme based on DM-OFDM-IM over an underwater magnetic induction communication system

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Optics Express 2025年第11期33卷 23342-23357页

作者： Jiyuan Wang Jianxin Ren Bo Liu Yaya Mao Xiumin Song Shuaidong Chen Xue Tang Lilong Zhao Rahat Ullah Institute of Optics and Electronics Nanjing University of Information Science & Technology Nanjing 210044 China State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science & Technology Nanjing 210044 China Beijing University of Posts and Telecommunications Beijing 100876 China Department of Electronic Engineering Tsinghua University Beijing 100084 China bo@*** Nanjing University of Posts and Telecommunications Nanjing 210003 China

This paper introduces a rotated 8QAM probabilistic shaping (PS) scheme based on dual-mode orthogonal frequency-division multiplexing with index modulation (DM-OFDM-IM) over an underwater magnetic induction (MI) communication system. The key aspect of DM-OFDM-IM is its use of two distinct signal constellations to modulate the carrier signal independently. We categorize the 8QAM constellations into internal and external groups. We divide the subcarriers within the whole bit block into two groups: the index selection group and the constellation mapping group. The internal constellation transmission probability is advanced by making the index bits of the index selection group correspond to different constellation modulations' times and order. The modulation index is structured to achieve a 3:1 ratio between the internal and external constellation signals. This approach enhances the likelihood of transmitting low-energy internal signals, thereby lowering the bit error rate (BER). Comparative analysis with the constant composition distribution matching (CCDM) method reveals no significant performance differences. Additionally, constellation rotation is integrated to improve signal robustness in Rayleigh fading channels, increasing diversity gain without expanding bandwidth or power consumption. To validate the scheme’s underwater performance, a practical experiment was conducted at 15 cm water depth, transmitting DM-OFDM-IM-based PS rotated 8QAM signals over a 23 cm distance at 62.18 Kb/s. Results demonstrate that constellation rotation significantly enhances signal reliability despite its simplicity. Compared to conventional 8QAM, the proposed method extends the communication distance by 4.6 cm at a hard-decision forward error correction (FEC) bit error rate (BER) limit of 3.8 × 10 −3 . This approach achieves high performance in MI communication with low complexity and ease of implementation, positioning it as a promising solution for future short-range underwater magnet

关键词： Bit error rate Frequency division multiplexing Modulation Orthogonal frequency-division multiplexing Signal processing Signal transmission

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Thunderstorm Prediction Method Based on CNN-BiLSTM Using BEADS

Thunderstorm Prediction Method Based on CNN-BiLSTM Using BEA...

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International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xu Yang Hongyan Xing Xinyuan Ji Jiangsu Key Laboratory of Meteorological Detection and Information Processing Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781665444927

Atmospheric electric field signal (AEFS) usually superimposes low-frequency noise, which has a negative effect on thunderstorm monitoring. A thunderstorm prediction method based on Convolutional Neural Network (CNN) and Bidirectional Long Short Term Memory (BiLSTM) is proposed. Firstly, AEFS is divided into useful, baseline and noise components by BEADS. After getting the estimated value of the useful signal, the denoised signal is obtained. Then, the AEFS prediction model is built based on BiLSTM. After inputting the AEFS spatial features extracted by CNN into the model, a CNN-BiLSTM hybrid model for thunderstorm prediction is formed. After analyzing the performance of the method, we carried out the experiment in thunderstorm weather. Results show that the SNR of AEFS processed by BEADS is improved effectively. It's worth noting that the determining coefficients before and after BEADS are all above 94.12%, showing a good effect. Finally, the effectiveness of the method is proved again by the coincidence between the predicted results and the radar chart.

关键词： Instruments Radar Predictive models Feature extraction Low-frequency noise Convolutional neural networks Monitoring

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Three-dimensional constellation design based on centroid-corrected geometric shaping with optimized average Hamming distance

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Optics Express 2025年第12期33卷 25094-25105页

作者： Chen Wang Bo Liu Jianxin Ren Yaya Mao Xiumin Song Shuaidong Chen Jianye Zhao Yu Bai Haojun Liu Yongyi Yu Chuanxi Zhang Rahat Ullah Institute of Optics and Electronics Nanjing University of Information Science & Technology Nanjing 210044 China State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science & Technology Nanjing 210044 China Beijing University of Posts and Telecommunications Beijing 100876 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Nanjing University of Posts and Telecommunications Nanjing 210003 China

In this paper, a novel (to our knowledge) three-dimensional (3D) constellation design based on centroid-corrected geometric shaping (CCGS) with optimized average Hamming distance (OAHD) is proposed, referred to as 3D-CCGS-OAHD. This scheme employs a centroid-correction technique to optimize the constellation point distribution and ensure a balanced geometry for higher constellation figure of merit (CFM). Meanwhile, a simulated annealing (SA) algorithm is used to minimize the average Hamming distance (AHD) between adjacent constellation points and explore a better bit-to-symbol mapping strategy superior to Gray mapping to improve the bit error rate (BER) performance. The 3D-CCGS-OAHD scheme was successfully demonstrated over a 2 km 7-core fiber. Results show that the 3D-CCGS constellation achieves a sensitivity gain of 0.84 dB compared to the traditional 3D constellation under Gray mapping. In addition, the 3D-CCGS-OAHD scheme achieves a gain of 1.29 dB compared to the traditional 3D constellation. The experiment results demonstrate that the proposed scheme is suitable for short-distance optical communication systems and has promising research prospects.

关键词： Frequency division multiplexing Optical signals Optical systems Phase modulation Quadrature amplitude modulation Variable optical attenuators

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A study on evanescent wave humidity sensor based on PEG-PMMA microspheres with enhanced performance

IEEE Photonics Journal

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IEEE Photonics Journal 2025年第3期17卷

作者： Chen, Yuxin Qi, Yutong Zhu, Bao Zhou, Xingchen Xiao, Xuefei Gu, Zheyuan Qian, Jun He, Chuanyang Lai, Min Ma, Yan Liu, Bo Nanjing University of Information Science & Technology State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing 210044 China Nanjing University of Information Science & Technology NUIST Reading Academy Nanjing 210044 China Nanjing University of Information Science & Technology School of Physics and Optoelectronic Engineering Nanjing 210044 China

In this study, we demonstrate fabrication of an evanescent wave fiber optic humidity sensor based on PEG-PMMA microsphere film as moisture-sensitive material. A three dimensional stacking structure of PEG-PMMA microspheres is formed by dip coating method on fiber core. A simultaneous fast response and recovery is optimized with equilibrium time of 13 s and 8 s between 30% RH and 80% RH, respectively. The sensor possessed a maximum sensitivity of 157.143 lux/% RH in the range of 70–80% RH and a good linear relationship between the logarithm of output optical intensity and relative humidity with a correlation coefficient of 0.998. Moreover, the sensor exhibits low hysteresis, excellent repeatability, short-term and long-term stability and electromagnetic immunity. Modulation of intensity is primarily attributed to scattering of evanescent wave on polymer microspheres in humidity sensing. © 2009-2012 IEEE.

关键词： Evanescent wave fiber optic sensor PMMA microspheres relative humidity

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Hardware acceleration implementation of a ground-based cloud image classification algorithm

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Journal of Electronic Measurement and Instrumentation 2025年第2期39卷 21-31页

作者： Lin, Feng Wenqiang, Song Wei, Xu Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and Technology Nanjing210044 China

The automatic observation and recognition of ground-based clouds have guiding significance for analyzing atmospheric motion trends and weather forecasting. To solve the problem of low accuracy of ground-based cloud image classification algorithms and difficulties in deploying them on embedded terminals, a ground-based cloud image classification network model GBcNet based on residual network structure and a hardware implementation architecture based on ZYNQ are proposed. The PS end is used to load the weight parameters and cloud data of the model, and the PL end implements DDR3 read-write control and GBcNet hardware acceleration. For the GBcNet network, accelerated IP cores corresponding to each module were designed, including sliding window, convolutional layer, pooling layer, batch normalization layer, and fully connected layer. Experiments were conducted on the CCSN dataset, and the results showed that the GBcNet model achieved an accuracy of 96. 02% on a PC platform. After hardware acceleration, the accuracy remained at 94. 5%. Compared with the recognition rate of the PC model, the accuracy loss for each cloud class did not exceed 3%, and the overall accuracy loss was less than 1. 5%. The maximum resource usage on the FPGA did not exceed 48%, and the inference time for a single ground-based cloud image was 0. 13 seconds. Compared to existing ground-based cloud recognition methods, this approach demonstrates higher accuracy and shorter inference time. The proposed recognition model and acceleration method provide a reference solution for the development of multi-node, portable ground-based cloud observation equipment. © 2025 Editorial Office of EMI Journal. All rights reserved.

关键词： Motion analysis

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Expressions of Electron Escape Probability and Photo-Emission from Metals

SSRN

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SSRN 2023年

作者： Liu, Yi-Fan Xie, Ai-Gen Tang, Jing Dong, Hong-Jie School of Physics and Optoelectronic Engineering Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu international Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing210044 China School of Teacher Education Nanjing University of Information Science & Technology Nanjing210044 China

According to existing formulas and the fact that thermal emission, secondary electron emission and photo-emission PE have common mechanisms of escape, the expressions of electron escape probability of several kinds of emitters are determined. From the determined expression of the mean probability that an interior photo-emitted electron escapes into vacuum after arriving at metal surface, existing formulas, characteristics of PE and experimental data, the formulas for spectra of photo- emitted electrons f, B, λ, mean energy of photo-emitted electrons and AQ of metals near threshold frequency γ0 and farther away γ0 were deduced and proved correct, respectively;where B is the mean probability that an interior photo-emitted electron escapes into vacuum after arriving at metal surface, λ is the mean escape depth of photo-emitted electrons from metals, AQ is absolute quantum efficiency. The C γ calculated with the deduced formula for AQ were analyzed, it concludes that the calculated C γ are correct, C γ is the mean probability that one electron of the conduction band of a given metal absorbs one given frequency photon. Based on the universal formula for λ of photo-emitted electrons undergoing PE from metals near γ0, the deduced formula for AQ of metals near γ0 and corresponding parameters, several special formulas for λ of photo-emitted electrons undergoing PE from Au and Ni near γ0 were obtained, respectively. © 2023, The Authors. All rights reserved.

关键词： Secondary emission

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