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Social Media-Based Surveillance systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Simulation of random fiber Bragg grating array in polarization-maintaining fiber based on photonic localization effect

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Optoelectronics Letters 2024年第8期20卷 460-471页

作者： LI Zhihan HE Wei LI Shaode Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology UniversityBeijing 100192China Beijing Laboratory of Optical Fiber Sensing and System Beijing Information Science and Technology UniversityBeijing 100192China

Mid-infrared wavelength switchable and dual-wavelength random laser output has many potential applications.A polarization-maintaining random fiber Bragg grating(PMRFBG)array based on the photonic localization effect of longitudinal invariant transverse disorder in fiber structure is proposed,which can be used as random feedback of dual-wavelength and wavelength switchable output of random fiber laser(RFL).The random fiber Bragg grating(RFBG)array was designed on the panda-type polarization-maintaining fiber(PMF),and the two center wavelengths were 2151.60 nm and 2152.22 nm,*** RFBG array was designed on the bow tie-type PMF,and the two center wavelengths were obtained,which were 2153.08 nm and 2153.96 nm,*** RFBG array with a center wavelength of 2139.27 nm was designed on single-mode fiber(SMF).The length of individual fiber Bragg grating(FBG)and PMRFBG,the refractive index modulation depth,the number of cascaded gratings,and the distance between gratings have different effects on the full width at half maximum(FWHM)and reflectance of the RFBG and PMRFBG array,but not on the central wavelength,as obtained by simulation using the transmission matrix *** designed PMRFBG array provides theoretical support for the design of the feedback mechanism of RFL.

关键词： fiber polarization random

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Design and simulation of a silicon-based hybrid integrated optical gyroscope system

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Chinese Physics B 2023年第4期32卷 397-404页

作者：孙道鑫张东亮鹿利单徐涛郑显通周哲海祝连庆 Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science&Technology UniversityBeijing 100192China Beijing Laboratory of Optical Fiber Sensing and System Beijing Information Science&Technology UniversityBeijing 100016China

By combining a silicon-based lithium niobate modulator and a silicon-based Si3N4resonator with silicon-based photonics technology,a highly systematic design of a hybrid integrated optical gyroscope with enhanced reciprocity sensitivity and a dual micro-ring structure is proposed for the first time in this *** relationship between the device's structural parameters and optical performance is also analyzed by constructing a complete simulation link,which provides a theoretical design reference to improve the system's *** the wavelength is 1550 nm,the conversion frequency of the dual-ring optical path is 50 MHz,the coupling coefficient is 0.2,and the radius R is 1000μm,the quality factor of the silicon-based Si_(3)N_(4)resonator is 2.58×10^(5),which is 1.58 times that of the silicon-on-insulator ***,the effective number of times the light travels around the ring before leaving the micro-ring is 5.93,which is 1.62 times that of the silicon-on-insulator *** work fits the gyro dynamic output diagram,and solves the problem of low sensitivity at low speed by setting the phase *** results provide a basis for the further optimization of design and chip processing of the integrated optical gyroscope.

关键词： silicon photonics integrated optical gyroscope micro-ring resonator Sagnac effect

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Collaborative Service Provisioning for UAV-Assisted Mobile Edge Computing

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Chinese Journal of Electronics 2024年第6期33卷 1504-1514页

作者： Yuben QU Zhenhua WEI Zhen QIN Tao WU Jinghao MA Haipeng DAI Chao DONG The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Colllege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Xi'an Research Institute of High Technology Department of Information and Communication Noncommissioned Officer Academy of PAP National University of Defense Technology Department of Computer Science and Technology Nanjing University

Unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC), as a way of coping with delaysensitive and computing-intensive tasks, is considered to be a key technology to solving the challenges of terrestrial MEC networks. In this work, we study the problem of collaborative service provisioning(CSP) for UAV-assisted MEC. Specifically, taking into account the task latency and other resource constraints, this paper investigates how to minimize the total energy consumption of all terrestrial user equipments, by jointly optimizing computing resource allocation, task offloading, UAV trajectory, and service placement. The CSP problem is a non-convex mixed integer nonlinear programming problem, owing to the complex coupling of mixed integral variables and non-convexity of CSP. To address the CSP problem, this paper proposes an alternating optimization-based solution with the convergence guarantee as follows. We iteratively deal with the joint service placement and task offloading subproblem, and UAV movement trajectory subproblem, by branch and bound and successive convex approximation, respectively,while the closed form of the optimal computation resource allocation can be efficiently obtained. Extensive simulations validate the effectiveness of the proposed algorithm compared to three baselines.

关键词： Energy consumption Multi-access edge computing Collaboration Programming Autonomous aerial vehicles Minimization Trajectory Resource management Optimization Convergence

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Single-Valued Neutrosophic Graph with Heptapartitioend Structure

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Neutrosophic Sets and systems 2025年 80卷 728-748页

作者： Fathi, Hanaa Myvizhi, M. Abdelhafeez, Ahmed Abdellah, Mohamed Refaat Eassa, Mohamed Sawah, Mohamed S. Elbehiery, Hussam College of Information Technology Amman Arab University Amman Jordan KPR Institute of Engineering and Technology Tamilnadu Coimbatore India 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 The Department of Computer Science College of Information Technology Misr University for Science and Technology Cairo Egypt Department of Computer Science Faculty of Information Technology Ajloun National University P.O.43 Ajloun26810 Jordan

This study applies single-valued neutrosophic sets, which extend the frameworks of fuzzy and intuitionistic fuzzy sets, to graph theory. We introduce a new category of graphs called Single-Valued Heptapartitioned Neutrosophic Graphs (SVHNG) and investigate their characteristics through comprehensive proofs and illustrative examples. © 2025, University of New Mexico. All rights reserved.

关键词： Heptapartitioend Neutrosophic Set Neutrosophic Graph Neutrosophic Sets SVHN-Graph

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Soft-GNN:towards robust graph neural networks via self-adaptive data utilization

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Frontiers of Computer science 2025年第4期19卷 1-12页

作者： Yao WU Hong HUANG Yu SONG Hai JIN National Engineering Research Center for Big Data Technology and System Service Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China College of Information and Communication National University of Defense TechnologyWuhan 430019China Department of Computer Science and Operations Research Universitéde MontréalMontreal H3C 3J7Canada

Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.

关键词： graph neural networks node classification label noise robustness

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TransFlowGAN: Generation and Balancing of Network Traffic Data 24

TransFlowGAN: Generation and Balancing of Network Traffic Da...

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2024 Asia Pacific Conference on Computing Technologies, Communications and Networking, CTCNet 2024

作者： Zhang, Hongzheng National Key Laboratory of Science and Technology on Information System Security China

ISBN: (纸本)9798400709609

In recent years, with the rapid development of deep learning technology, researchers in the field of network security have begun to explore the use of deep learning to solve the problem of encrypted traffic classification. However, existing publicly available encrypted traffic datasets suffer from severe class imbalance issues, which significantly impact the performance of deep learning classification methods. Constructing a complete encrypted traffic dataset from scratch is both time-consuming and costly. To address this issue, this paper proposes an innovative model named TransFlowRGAN, which is an encrypted traffic sequence feature generation model that combines Transformer and Relative Generative Adversarial Network (RGAN). Our model leverages the advantages of RGAN, effectively mitigating the instability and mode collapse issues that traditional GAN models often encounter during training. Additionally, it incorporates the Transformer architecture. The self-attention mechanism of the Transformer can better capture the complex features and long-term dependencies in traffic data, resulting in the generation of higher-quality data. We evaluated the performance of our model on the ISCXVPN2016 public dataset. The results demonstrate that TransFlowRGAN excels in handling imbalanced datasets, significantly outperforming other data augmentation models. © 2024 Copyright held by the owner/author(s).

关键词： Generative adversarial networks

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Security Testing for Deep Learning Models in Multiple Scenarios 3rd

Security Testing for Deep Learning Models in Multiple Scenar...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Wu, Zhendong Li, Hu Zhang, Ming Lu, Shuaibing National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9789819624676

Deep learning models are widely used in security-sensitive tasks such as facial recognition and autonomous driving. Security issues in deep models could have serious implications for people’s lives, such as life-threatening situations resulting from autonomous driving failures. To enhance the security of deep models, security testing is necessary before their formal deployment. Since different scenarios may involve different deep models, a security testing method that targets multiple scenarios would be more universally applicable. In this paper, we propose a security testing method for deep models that can be applied across multiple scenarios, primarily utilizing adversarial attacks to test the models. For the deep model under test, we first construct threat scenarios and then associate the model with datasets and adversarial attack methods. Subsequently, we generate adversarial examples to input into the deep model to check its accuracy in classification. Finally, we evaluate the success rate of adversarial attacks on the deep model. A high attack success rate indicates low model security, necessitating developers to employ adversarial training or other methods to enhance model security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12572-12587页

作者： Lin, Qinjie Sun, Hao Xu, Yanjie Wang, Junyu Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

Automatic target recognition (ATR) is crucial for synthetic aperture radar (SAR) image interpretation. However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. Moreover, SAR ATR typically follows the closed set assumption, but in dynamic and open real-world environments, SAR systems may encounter target classes that have not been seen during training. To address these issues, this paper proposes a SAR open set recognition (OSR) method that combines local electromagnetic scattering and global structure features. The global structural features focus on the overall relationship between target and background, while the local electromagnetic scattering features can effectively capture the scattering characteristics of target. Hence, we construct a global and local feature guidance (GLGE) network, fuses these complementary features as prior knowledge to guide deep features. Then, a class-anchor-based loss function is constructed by Anchor loss and Tuple loss, which cluster the features of known classes targets around predefined class anchors. Finally, the distance ratio is calculated to identify known classes targets and reject unknown classes targets. The experimental results on the MSTAR and SAR-ACD datasets show that our method outperforms other OSR methods in recall, precision, F1, and accuracy, demonstrating a superior performance in OSR. © 2008-2012 IEEE.

关键词： Automatic target recognition

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AWG-based large dynamic range fiber Bragg grating interrogation system

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Optoelectronics Letters 2024年第3期20卷 129-134页

作者： LI Shufeng YUAN Pei LI Ke LI Ting ZHU Lianqing Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science&Technology UniversityBeijing 100192China Beijing Laboratory of Optical Fiber Sensing and System Beijing Information Science&Technology UniversityBeijing 100016China

Arrayed waveguide gratings(AWGs) are extensively employed in fiber Bragg grating(FBG) interrogation systems due to their compact size, lightweight nature, and excellent interrogation performance. The resolution and total measurement range of AWG-based FBG interrogation systems are constrained by the output properties of AWG. We proposed an AWG-based large dynamic range interrogation system. The temperature dependence of AWG is exploited to achieve continuous interrogation. The test results show that the interrogation system has a dynamic range of 28.67 nm, an interrogation accuracy better than 25 pm, and a wavelength resolution of 6 pm.

关键词： fiber waveguide AWG

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