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Research Progress on Solar Flare Forecast Methods Based on Data-driven Models

Research in Astronomy and Astrophysics 2023年第6期23卷 12-27页

作者： Ke Han Meng-Yao Yu Jun-Feng Fu Wen-Bin Ling De-quan Zheng Jie Wan Peng E School of Computer and Information Engineering Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information ProcessingHarbin University of CommerceHarbin 150028China Laboratory for Space Environment and Physical Sciences Harbin Institute of TechnologyHarbin 150001China

Eruption of solar flares is a complex nonlinear process,and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based *** far,there are not reliable physical models to accurately account for the flare outburst mechanism,but a lot of data-driven models have been built to study a solar flare and forecast *** the paper,the status of solar-flare forecasting is reviewed,with emphasis on the machine learning methods and data-processing techniques used in the *** first,the essential forecast factors strongly relevant to solar flare outbursts,such as classification information of the sunspots and evolution pattern of the magnetic field,are reviewed and ***,methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare ***,typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models,and the forecast performances of the different models are ***,we herein summarize the current research on solar flare forecasting and outline its development trends.

关键词： Sun:activity Sun:flares (Sun:)sunspots Sun:magnetic fields

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Efficient video summarization through MobileNetSSD: a robust deep learning-based framework for efficient video summarization focused on objects of interest

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Multimedia Tools and Applications 2024年 1-26页

作者： Yarrarapu, Manasa Leelavathy, Narkedamilly Haritha, Dasari Department of Computer Science and Engineering Jawaharlal Nehru Technological University Andhra Pradesh Kakinada533003 India Department of Computer Science and Engineering Godavari Institute of Engineering and Technology Andhra Pradesh Rajahmundry533296 India Department of Computer Science and Engineering University College of Engineering Jawaharlal Nehru Technological University Andhra Pradesh Kakinada533003 India

Now-a-days, the generation of videos has increased dramatically due to the quick growth of multimedia and the internet. The need for effective ways to store, manage, and index the massive numbers of videos has become imperative due to this expansion. As a result, a method needs to be proposed that collects only the necessary data from the original recording. In computer vision, Video summarization is a significant task, and its primary goal is to give a quick summary of the video by removing irrelevant information and capturing key frames from the video. Many approaches have developed over the last several decades, using the most recent deep neural network architectures that represent the current state-of-the-art. Our method involves extracting vital key frames from the input video using the MobileNetSSD model, which is well-known for its efficient recognition and localization of objects of interest. These highlighted frames are essential in creating a detailed video summary. Furthermore, a method of temporal analysis is applied to guarantee that the summary accurately reflects the relevant events in the order in which they occurred, contributing to a coherent and meaningful representation of the information. We evaluated the proposed approach on TV Sum and SUM me video datasets, comparing the results against cutting-edge video summarization techniques. Our approach works effectively to produce clear and meaningful video summaries. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Network architecture

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Three-dimensional macroscopic absorbents: From synergistic effects to advanced multifunctionalities

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Nano Research 2024年第3期17卷 1952-1983页

作者： Shijie Zhang Di Lan Xingliang Chen Yueyuan Gu Junwen Ren Suxuan Du Shichang Cai Xiaomiao Zhao Zhiwei Zhao Guanglei Wu School of Material Science and Engineering Henan University of TechnologyZhengzhou 450001China School of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China Key Laboratory of Clean Dyeing and Finishing Technology of Zhejiang Province Shaoxing UniversityShaoxing 312000China School of Resources Environment and Safety Engineering University of South ChinaHengyang 421001China College of Electrical Engineering Sichuan UniversityChengdu 610065China Institute of Materials for Energy and Environment State Key Laboratory of Bio-fibers and Eco-textilesCollege of Materials Science and EngineeringQingdao UniversityQingdao 266071China Key Laboratory of Engineering Dielectrics and Its Application Ministry of EducationSchool of Electrical&Electronic EngineeringHarbin University of Science and TechnologyHarbin 150080China

The accelerated arriving of 5G era has brought a new round of intelligent transformation which will completely emancipate smart terminal *** the subsequent deleterious effect of electromagnetic wave on electronic devices is increasingly serious,driving the growth of next-generation electromagnetic wave *** a tactful combination of components and structures,three-dimensional(3D)macroscopic absorbents with fascinating synergy afford exceptional electromagnetic wave absorption,and tremendous efforts have been devoted to this ***,in terms of macroscopic absorbents and their synergistic effect,few reviews are proposed to comb the latest achievements and detailed *** review article focuses on the synergistic effect of macro-architectured absorbents mainly including structure-induced synergy,structure-components synergy,and multiple-components induced *** then the potential construction principles and strategies of macroscopic absorbents are ***,the key information for structures and components manipulation including nano-micro design and components regulation is further dissected by critically selected cutting-edge 3D macroscopic ***,a brief summary of multifunctional electromagnetic wave absorbents(EWAs)-based macroscopic structures is ***,the development prospects and challenges of these materials are discussed.

关键词： three-dimensional(3D)structures synergistic effect electromagnetic wave absorption absorption mechanism multifunction

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Research on Ultrasonic Stress Precision Measurement Method 5

Research on Ultrasonic Stress Precision Measurement Method

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Liu, Enxiao Song, Youfan Gu, Wenhao Liu, Yongmeng Zheng, Jinde School of Mechanical Engineering Anhui University of Technology Ma'anshan China School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9798331529192

Accurate measurement of stress in key components is a necessary guarantee for improving the comprehensive performance and operational safety of high-end equipment. In order to improve the accuracy of stress measurement, this paper proposes an ultrasonic stress precision measurement method that considers temperature changes. This method adds a feedback transducer between the ultrasonic transmission and reception transducers, which receives longitudinal wave signals containing temperature and stress change information through the feedback transducer. The temperature and stress information were calculated based on the longitudinal wave acoustic time difference (ultrasonic propagation time difference) Δ tF and critical refracted longitudinal wave (LCR wave) acoustic time difference Δ tR, thus separating the stress measurement error caused by temperature changes. The research results indicate that the maximum stress measurement error of this method is 2.302 MPa, which effectively improving the accuracy of stress measurement. © 2024 IEEE.

关键词： Stress measurement

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Design and Implementation of Indoor Visual Autonomous Navigation System for Quadrotor UAV Based on Binocular Camera and IMU 3

Design and Implementation of Indoor Visual Autonomous Naviga...

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3rd International Conference on computer science, Electronic Information engineering and Intelligent Control technology, CEI 2023

作者： Tang, Jiaze Guo, Tianxing Liudan Li, Junbao Sun, Jinwei Huang, Wenbin Wang, Qisong Electrical Measurement Technology and Intelligent Control Institute School of Instrumention Science and Engineering Harbin Institute of Technology Harbin150080 China Schools of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9798350372052

Addressing the challenge of unmanned aerial vehicles (UAVs) navigating indoors without satellite positioning, this study introduces a novel method combining binocular camera and inertial measurement unit (IMU) data. This approach overcomes the structural differences between visual and inertial information, integrating them effectively for enhanced indoor autonomous navigation. The research presents a gradient-free path planning framework, pivotal for enhancing the UAV's ability to execute efficient and stable flight in intricate indoor settings. The cornerstone of this system is an advanced path planning algorithm, adept at swiftly identifying optimal routes and adapting to environmental shifts. The system's efficacy was rigorously evaluated through simulations and real-world tests, confirming its precision in positioning and path planning without reliance on satellite data. The findings demonstrate the system's capacity for precise localization and effective route determination, utilizing an integration of visual and inertial inputs. This research significantly contributes to the autonomous flight capabilities of UAVs, offering a valuable reference for future UAV autonomous navigation systems. By delving into visual-inertial fusion navigation technology, the study paves the way for expanded indoor UAV applications. © 2023 IEEE.

关键词： Antennas

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Electrochemical extraction of strontium from molten salts using reactive zincand aluminum electrodes

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International Journal of Minerals,Metallurgy and Materials 2025年第4期32卷 892-901页

作者： Yongcheng Zhang Taiqi Yin Lei Zhang Xiaochen Zhang Tao Bo Xiaoli Tan Mei Li Wei Han Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201China College of Materials Science and Chemical Engineering Harbin Engineering UniversityHarbin 150001China MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China Qianwan Institute of CNITECH Ningbo 315336China

Herein, the electrochemical behaviors of Sr on inert W electrode and reactive Zn/Al electrodes were systematically investig-ated in LiCl–KCl–SrCl2molten salts at 773 K using various electrochemical methods. The chemical reaction potentials of Li and Sr on re-active Zn/Al electrodes were determined. We observed that Sr could be extracted by decreasing the activity of the deposited metal Sr onthe reactive electrode, although the standard reduction potential of Sr(II)/Sr was more negative than that of Li(I)/Li. The electrochemicalextraction products of Sr on reactive Zn and Al electrodes were Zn13Sr and Al4Sr, respectively, with no codeposition of Li *** on the density functional theory calculations, both Zn13Sr and Al4Sr were identified as stable intermetallic compounds with Zn-/Al-rich phases. In LiCl–KCl molten salt containing 3wt% SrCl2, the coulombic efficiency of Sr in the Zn electrode was ~54%. The depolar-ization values for Sr on Zn and Al electrodes were 0.864 and 0.485 V, respectively, exhibiting a stronger chemical interaction between Znand Sr than between Al and Sr. This study suggests that using reactive electrodes can facilitate extraction of Sr accumulated while elec-trorefining molten salts, thereby enabling the purification and reuse of the salt and decreasing the volume of the nuclear waste.

关键词： strontium reductive extraction molten salt depolarization effect reactive electrode

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Strengthening mechanism of B_4C@APC/Al matrix composites reinforced with bimodal-sized particles prepared by hydrothermal carbonized deposition on chips

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Journal of Materials science & technology 2022年第28期123卷 60-69页

作者： Yingjie He Hongyu Xu Yang Liu Yihan Chen Zesheng Ji School of Material Science and Chemical Engineering Harbin University of Science and TechnologyHarbin 150040China Energy and Environment Engineering Institute Nanchang Institute of TechnologyNanchang 330044China College of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou 225127China

A B_(4)C@amorphous carbon(APC)/Al matrix composite was fabricated by using hydrothermal carbonized deposition on chips(HTCDC)process and solid-state synthesis *** microstructure and mechanical properties of the B_(4)C@APC/Al matrix composite were *** HTCDC process,nano-B_(4)C particles(50 nm)and micron-sized B_(4)C@APC core-shell spheres with a diameter of 2μm were found in the *** microhardness of the micron-sized B_(4)C@APC spheres is 1.66 GPa,which is greater than that of theα-Al matrix(1.06 GPa).Dislocation accumulation is observed around the micron-sized B_(4)C@APC spheres,indicating that the micron-sized B_(4)C@APC spheres have a strengthening effect on theα-Al *** to the formation of micron-sized B_(4)C@APC spheres,the reinforcement of nano-B_(4)C particles into the composites is transformed from single-sized particle enhancement to bimodal-sized particle *** strengthening mechanism for B_(4)C@APC/Al matrix composites with bimodalsized particles of nano-B_(4)C and micron-sized B_(4)C@APC spheres were analyzed,which includes thermal mismatch strengthening generated by the mismatch of coefficient of thermal expansion(CTE)between micron-sized B_(4)C@APC core-shell spheres andα-Al matrix,Orowan strengthening produced by nano-B_(4)C particles,Hall-Petch strengthening and load transfer strengthening produced by the bimodal-sized enhancement from nano and microspheres.A relationship model between the yield strength(YS)increment and the conversion rate(x)of micron-sized B_(4)C@APC core-shell spheres was estimated.

关键词： Bimodal-sized particle enhancement Micron-sized B_4C@APC core-shell spheres Al matrix composites Strengthening mechanism

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An Enhanced Integrated Method for Healthcare Data Classification with Incompleteness

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computers, Materials & Continua 2024年第11期81卷 3125-3145页

作者： Sonia Goel Meena Tushir Jyoti Arora Tripti Sharma Deepali Gupta Ali Nauman Ghulam Muhammad Electrical and Electronics Engineering(EEE)Department Maharaja Surajmal Institute of TechnologyNew-Delhi110058India Information Technology(IT)Department Maharaja Surajmal Institute of TechnologyNew-Delhi110058India Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Department of Computer Science and Engineering Yeungnam UniversityGyeongsan-si38541Republic of Korea Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11421Saudi Arabia

In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification *** approaches often rely on statistical methods for imputation,which may yield suboptimal results and be computationally *** paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved *** classification methods are ill-suited for incomplete medical *** enhance efficiency without compromising accuracy,this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete ***,the linear interpolation imputation method alongside an iterative Fuzzy c-means clustering method is applied and followed by a classification *** effectiveness of the proposed approach is evaluated using multiple performance metrics,including accuracy,precision,specificity,and *** encouraging results demonstrate that our proposed method surpasses classical approaches across various performance criteria.

关键词： Incomplete data nearest neighbor linear interpolation imputation clustering classification

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Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification

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computers, Materials & Continua 2024年第10期81卷 867-883页

作者： Mahesh Thyluru Ramakrishna Kuppusamy Pothanaicker Padma Selvaraj Surbhi Bhatia Khan Vinoth Kumar Venkatesan Saeed Alzahrani Mohammad Alojail Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India School of Computer Science and Engineering VIT-AP UniversityAmaravati522241India Department of Computer Science&Technology Madanapalle Institute of Technology&ScienceMadanapalle517325India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK School of Computer Science Engineering&Information Systems(SCORE) Vellore Institute of Technology(VIT)Vellore632014India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11531Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpuraPunjab140401India

Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within computer science and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.

关键词： Deep learning MRI brain tumor cassification EfficientNetB3 computational engineering healthcare technology artificial intelligence in medical imaging tumor segmentation neuro-oncology

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Graph-Based Spectro-Temporal Dependency Modeling for Anti-Spoofing 48

Graph-Based Spectro-Temporal Dependency Modeling for Anti-Sp...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Chen, Feng Deng, Shiwen Zheng, Tieran He, Yongjun Han, Jiqing Harbin Institute of Technology School of Computer Science and Technology China Harbin Normal University School of Mathematical Science China

ISBN: (纸本)9781728163277

A great deal of recent research reveals that artifacts introduced by spoofing algorithms reside in specific frequency subbands or temporal segments. Therefore, the performance of spoofing detection can be improved by focusing on these regions. However, it is difficult for the detection system to choose an appropriate region when it encounters an unknown spoofing algorithm, resulting in poor generalization. Actually, there is a noticeable difference in the inter-region relationship between the bonafide and spoofed speeches. We name the inter-region relationship spectro-temporal dependency and design a method to model it for anti-spoofing. By focusing on the general dependency difference rather than specific regions, the generalization ability of the detection system can be improved. We employ a graph neural network to model the dependency and incorporate prior knowledge into the graph by designing the graph structure and edge weight, which forces the network to pay more attention to potential relationships. In addition, an attention mechanism is introduced in the graph pooling to focus on more critical nodes. The proposed method achieves an equal error rate of 0.58% on the ASVspoof 2019 LA dataset and outperforms all competing systems. © 2023 IEEE.

关键词： Graphic methods

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