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2022 International Conference on Statistics, Data science, and Computational Intelligence, CSDSCI 2022

作者： Luo, Yanpeng Xiong, Jinyu Yang, Yuxiang Zhu, Mingjun Zhang, Tongxin Cheng, Haibing College of Information System Engineering PLA Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510661325

Formation target track sorting is an important problem in multi-target track processing. Unlike the processing of periodic scans and point tracks of active radar, passive positioning data has the problems of irregular positioning period and difficulty in distinguishing multiple targets by target signal attributes. In this paper, we propose a track initiation algorithm for passive positioning system based on density clustering and Hough transform for the characteristics of passive positioning system. The algorithm first uses the density clustering algorithm to identify the cluster centers of targets with large measurement errors, and then uses the Hough transform method to initiate a track. © 2023 SPIE.

关键词： Hough transforms

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FLyer: Federated Learning-based Crop Yield Prediction for Agriculture 5.0

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第07期6卷 1943-1952页

作者： Dey, Tanushree Bera, Somnath Mukherjee, Anwesha De, Debashis Buyya, Rajkumar Maulana Abul Kalam Azad University of Technology Department of Computer Science and Engineering West Bengal India Mahishadal Raj College Department of Computer Science West Bengal Mahishadal721628 India The University of Melbourne Research Visitor of the CLOUDS Lab School of Computing and Information Systems Australia Lab School of Computing and Information Systems ParkvilleVIC3052 Australia

Crop yield prediction is a significant area of precision agriculture. In this paper, we propose a crop yield prediction framework named FLyer, based on federated learning and edge computing. In FLyer, the soil and environmental data are locally processed inside the edge servers, and the model parameters are transmitted between the edge servers and the cloud with encrypted gradients. LSTM is used as the local and global models for data analysis. As the LSTM model can capture the temporal dependencies and hold the sequential nature of the data, we use LSTM in FLyer. By encrypting the gradients, the gradient information leakage ratio is reduced, and data privacy is protected. For gradient encryption, we use AES-256, and for data encryption during local storage we use RSA and AES-256. The results demonstrate that FLyer diminishes the latency by 39% and energy consumption by 40% than the conventional edge-cloud framework respectively. The experimental results show that the global model in FLyer achieves above 99% accuracy, precision, recall, and F1-score in crop yield prediction. The results also present that the local models also achieve >94% accuracy in crop yield prediction. © 2020 IEEE.

关键词： Federated learning

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Southern Hemisphere Volcanism Triggered Multi-year La Niñas during the Last Millennium

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Advances in Atmospheric sciences 2024年第4期41卷 587-592页

作者： Shangrong ZHOU Fei LIU School of Atmospheric Sciences Sun Yat-Sen University Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Educationand Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519082China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China

To explain the recent three-year La Niña event from 2020 to 2022,which has caused catastrophic weather events worldwide,Fasullo et al.(2023)demonstrated that the increase in biomass aerosol resulting from the 2019-20 Australian wildfire season could have triggered this multi-year La Niñ***,we present compelling evidence from paleo-proxies,utilizing a substantial sample size of 26 volcanic eruptions in the Southern Hemisphere(SH),to support the hypothesis that ocean cooling in the SH can lead to a multi-year La Niña *** research highlights the importance of focusing on the Southern Ocean,as current climate models struggle to accurately simulate the Pacific response driven by the Southern Ocean.

关键词： volcanic eruptions multi-year La Niñas Australian wildfire southern ocean cooling

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Nonlocal inverse design of an ultrasonic lens for underwater manipulation of orbital angular momentum

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Physical Review Applied 2024年第2期22卷 024070页

作者： Chuanxin Zhang Fei Dai Xue Jiang Dean Ta Department of Biomedical Engineering School of Information Science and Technology State Key Laboratory of Integrated Chips and System

Acoustic orbital angular momentum (OAM) beams hold potential for underwater communications, particle manipulation, and biomedical applications. However, adapting air-based OAM technologies to the underwater environment presents unique challenges. In the underwater environment, the medium cannot be considered acoustically soft, and commonly used ultrasound frequencies have shorter wavelengths compared with air, necessitating new design approaches. Conventional underwater ultrasonic lens design methods often rely on simplified models that neglect nonlocal interactions and diffraction within the structure, therefore leading to suboptimal performance. We introduce a novel nonlocal inverse design method by integrating the full-wave models with the nondominated sorting genetic algorithm II (NSGA-II). This approach diverges from conventional phase-based design by optimizing the physical structure of the lens to account for nonlocal interactions within the material. We experimentally demonstrate the performance when generating high-purity OAM beams underwater. Our experimental results show that this method can generate high-purity OAM beams underwater, achieving over 90% purity for the OAM beams of topological charges from m = 1 to m = 4. This is a significant improvement compared with traditional methods, which typically reach 70–89% purity. These findings highlight the practical applicability of our method for nonlocally designing the ultrasonic lens, paving the way for advancements in beam performance for various applications.

关键词： Acoustic wave phenomena Inverse problems Ultrasonics Underwater acoustics Acoustic metamaterials Lenses Angular momentum Ultrasound techniques

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Long-term spatiotemporal variations of ammonia in the Yangtze River Delta region of China and its driving factors

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Journal of Environmental sciences 2025年第4期150卷 202-217页

作者： Jingkai Xue Chengzhi Xing Qihua Li Shanshan Wang Qihou Hu Yizhi Zhu Ting Liu Chengxin Zhang Cheng Liu School of Environmental Science and Optoelectronic Technology University of Science and Technology of ChinaHefei 230026China Key Lab of Environmental Optics&Technology Anhui Institute of Optics and Fine MechanicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Department of Precision Machinery and Precision Instrumentation University of Science and Technology of ChinaHefei 230026China Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of ChinaHefei 230026China Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 200438China School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou 215009China

This study focuses on the spatiotemporal distribution,urban-rural variations,and driving factors of ammonia Vertical Column Densities(VCDs)in China’s Yangtze River Delta region(YRD)from 2008 to *** data from the Infrared Atmospheric Sounding Interfer-ometer(IASI),Generalized Additive Models(GAM),and the GEOS-Chem chemical transport model,we observed a significant increase of NH_(3)VCDs in the YRD between 2014 and *** spatial distribution analysis revealed higher NH_(3)concentrations in the northern part of the YRD region,primarily due to lower precipitation,alkaline soil,and intensive agricul-tural ***_(3)VCDs in the YRD region increased significantly(65.18%)from 2008 to *** highest growth rate occurs in the summer,with an annual average growth rate of 7.2%during the period from 2014 to *** emissions dominated NH_(3)VCDs during spring and summer,with high concentrations primarily located in the agricultural areas adjacent to densely populated urban *** within several large urban areas have been discovered to exhibit relatively stable variations in NH_(3)*** rise in NH_(3)VCDs within the YRD region was primarily driven by the reduction of acidic gases like SO_(2),as emphasized by GAM modeling and sensitivity tests using the GEOS-Chem *** concentration changes of acidic gases contribute to over 80%of the interannual variations in NH_(3)*** emphasizes the crucial role of environmental policies targeting the reduction of these acidic *** emission control is urgent tomitigate environmental hazards and secondary particulate matter,especially in the northern YRD.

关键词： Yangtze River Delta Ammonia Spatiotemporal distribution Driving factors

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Acoustic logic networks realized with non-Hermitian and nonlocal metagratings

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Physical Review Applied 2024年第2期22卷 024048-024048页

作者： Hanjie Xiao Chuanxin Zhang Ying Li Dean Ta Xue Jiang Department of Biomedical Engineering School of Information Science and Technology State Key Laboratory of Integrated Chips and System

This paper proposes the concept and demonstrates the realization of acoustic logic networks (ALNs), a system that performs various logic operations using sound waves. Unlike traditional systems with separate components, ALNs integrate multiple logic functionalities with a single platform, performing operations like and, or, and xor gates, similar to those used in electronic computers. The design of ALNs leverages the non-Hermitian and nonlocal metagratings. By considering the intricate nonlocal interaction within the structure, the metagratings are designed to operate at exceptional points (EPs) to achieve the desired logic functions. Two metagratings are cascaded to construct the acoustic logic module (ALM), which acts as the basic building block of an ALN. The effectiveness of ALNs is confirmed through theoretical calculations, numerical simulations, and experiments. We demonstrate the ability to perform complex logic operations and realize various multichannel computing functions with the ALN of different configurations. These results showcase precise control over sound waves and significantly enhanced computing capabilities. The proposed ALNs represent a significant step forward in acoustic computing. This technology has the potential to revolutionize fields where traditional electronic computing might be impractical due to size, energy efficiency, or environmental limitations.

关键词： Acoustic modeling Acoustic wave phenomena Nonlocality Acoustic metamaterials Devices for digital logic, storage & processing Metagratings Non-Hermitian systems Sound wave techniques

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An oceanographic data collection scheme using hybrid optimization for leakage detection during oil mining in mobility assisted UWSN

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Multimedia Tools and Applications 2024年第42期83卷 89723-89741页

作者： Choudhary, Monika Goyal, Nitin Gupta, Deepali Sharma, Bhanu Sharma, Nonita Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Seth Jai Parkash Mukandlal Institute of Engineering and Technology Haryana Radaur India Department of Computer Science and Engineering School of Engineering and Technology Central University of Haryana Haryana Mahendragarh India Department of Information Technology Indira Gandhi Delhi Technical University for Women Delhi India Immersive and Interactive Technology Lab Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

Data acquisition is the process of collecting, measuring and analysing information using standardised, validated techniques for application-specific tasks. In mobility-assisted underwater wireless sensor networks (UWSNs), where nodes are not fixed due to water current of 3 m/sec, data collection becomes an arduous task. There are few works that provide a mobile sink with optimised data transmission path planning and scheduling. These systems do not transmit the data fast enough to provide real-time data transmission as these methods do not consider the buffer occupancy rate and latency in data acquisition. In this paper, a stimulating transmission path planning technique for mobile sinks using the hybrid Grey Wolf Optimizer Whale Optimization Algorithm (GWOWOA) is proposed. In contrast to other optimization techniques, this hybrid technique includes a number of update processes such as random position update, prey search by the Grey Wolf Optimizer (GWO) and prey search by the Whale Optimization Algorithm (WOA). In this paper, the fitness function is calculated in terms of distance to the mobile sink, buffer occupancy rate, energy level and data acquisition latency. The use of these variables makes the proposed technique innovative. To prove the efficiency of the proposed system, GWOWOA is compared with existing systems. The simulation results show that the proposed system increases the residual energy and accuracy of the collected data and minimises the delay. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Data acquisition

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Hydrothermal growth of regular ZnO nanoflowers for superhigh-detectivity ultraviolet photodetector application

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Optoelectronics Letters 2025年

作者： ZENG Weiwei YUAN Zhaolin HE Jianfeng WANG Xueyuan School of Information Engineering， East China University of Technology Jiangxi Engineering Technology Research Center of Nuclear Geosciense Date Science and System

In this work， a facile hydrothermal method was used to grow ZnO nanoflowers onto an interdigital patterned fluorine-doped tin oxide （FTO） glass substrate， the crystal structure and morphology of the sample were first investigated. The results showed that a great number of regular ZnO nanoflowers grew onto the substrate. Furthermore， the ZnO nanoflowers were used as photosensitive layers， a ultraviolet （UV） photodetector was achieved， its UV sensing performance was evaluated in detail. The results indicated that this ZnO nanoflowers UV photodetector exhibited good response to 365 nm UV light， its responsivity and detectivity were up to 135.5 A/W （5 V） and 1.5 × 1013Jones， respectively， the response speed was rapid （4.96 s）. This work explored a new way for achieving the high-performance nanostructured ZnO UV photodetectors.

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Synergy of machine learning and Mie-tronics: tailoring resonant response of meta-atom on demand 28

Synergy of machine learning and Mie-tronics: tailoring reson...

引用

Integrated Optics: Devices, Materials, and Technologies XXVIII 2024

作者： George, Renee C. Sedeh, Hooman Barati Lai, Fangxing Li, Hao Li, Wenhao Gao, Jiannan Sun, Jingbo Xiao, Shumin Kuznetsov, Arseniy Litchinitser, Natalia M. Department of Electrical and Computer Engineering Duke University DurhamNC United States Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen Shenzhen518055 China School of Materials Science and Engineering Tsinghua University Beijing100084 China A*STAR Institute Singapore Singapore

ISBN: (纸本)9781510670389

Optical metasurfaces are engineered 2D electromagnetic structures enabling flat optical elements with properties not readily found in nature. Their unit cells, meta-atoms, usually are represented by a set of electric and magnetic multipoles. All-dielectric-based metasurfaces have recently attracted significant attention owing to their virtually lossless transmission properties at optical frequencies. A majority of reported dielectric metamaterials are composed of relatively simple meta-atoms such as spheres, cubes, and cylinders, whose electromagnetic response is dominated by the electric dipole. However, magnetic dipoles and higher-order multipoles may enable new optical properties and functionalities, including directional scattering, beam steering, and new frequency generation. Despite impressive progress in the field of optical metamaterials and nanofabrication technologies, engineering meta-atoms that support such higher-order resonances is still challenging. Here, we demonstrate that designed titanium dioxide meta-atoms can enable dominant magnetic dipole response. We apply a machine-learning model to predict a meta-atom shape with a strong magnetic dipole resonant mode at the operating wavelength of 750 nm. Using finite-element-based numerical simulations implemented in COMSOL Multiphysics, we found that the optimized meta-atom is robust against experimental variations and conditions such as a non-perfectly collimated incident beam, nanofabrication inaccuracies, and an added substrate. The meta-atoms have been fabricated using two approaches, focused ion beam lithography and an electron beam lithography followed by reactive ion etching, and characterized using white light spectroscopy. To the best of our knowledge, this is the first experimental realization of a machine-learning-based optimization of a magnetic dipole mode at optical frequencies. © 2024 SPIE.

关键词： Atoms

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