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An Improved Northern Goshawk Optimization Algorithm for Feature Selection

Journal of Bionic Engineering 2024年第4期21卷 2034-2072页

作者： Rongxiang Xie Shaobo Li Fengbin Wu State Key Laboratory of Public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China State Key Laboratory of Public big data Guizhou UniversityGuiyang550025China

Feature Selection(FS)is an important data management technique that aims to minimize redundant information in a *** work proposes DENGO,an improved version of the Northern Goshawk Optimization(NGO),to address the FS *** NGO is an efficient swarm-based algorithm that takes its inspiration from the predatory actions of the northern *** order to overcome the disadvantages that NGO is prone to local optimum trap,slow convergence speed and low convergence accuracy,two strategies are introduced in the original NGO to boost the effectiveness of ***,a learning strategy is proposed where search members learn by learning from the information gaps of other members of the population to enhance the algorithm's global search ability while improving the population ***,a hybrid differential strategy is proposed to improve the capability of the algorithm to escape from the trap of the local optimum by perturbing the individuals to improve convergence accuracy and *** prove the effectiveness of the suggested DENGO,it is measured against eleven advanced algorithms on the CEC2015 and CEC2017 benchmark functions,and the obtained results demonstrate that the DENGO has a stronger global exploration capability with higher convergence performance and ***,the proposed DENGO is used for FS,and the 29 benchmark datasets from the UCL database prove that the DENGO-based FS method equipped with higher classification accuracy and stability compared with eight other popular FS methods,and therefore,DENGO is considered to be one of the most prospective FS ***'s code can be obtained at https://***/matlabcentral/fileexchange/158811-project1.

关键词： Northern goshawk optimization Learning strategy Hybrid differential strategy Numerical optimization Feature selection

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Blockchain-Based Key Management Scheme Using Rational Secret Sharing

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Computers, Materials & Continua 2024年第4期79卷 307-328页

作者： Xingfan Zhao Changgen Peng Weijie Tan Kun Niu State Key Laboratory of Public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Guizhou big data Academy Guizhou UniversityGuiyang550025China

Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a research focus for blockchain private key *** security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset *** threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public *** design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public *** proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart *** to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.

关键词： Blockchain smart contract rational secret sharing key management

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Effects of vacancy and external electric field on the electronic properties of the MoSi_(2)N_(4)/graphene heterostructure

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Chinese Physics B 2024年第3期33卷 542-550页

作者：梁前罗祥燕钱国林王远帆梁永超谢泉 college of big data and Information Engineering Institute of New Optoelectronic Materials and TechnologyGuizhou UniversityGuiyang 550025China

Recently,the newly synthesized septuple-atomic layer two-dimensional(2D)material MoSi_(2)N_(4)(MSN)has attracted attention *** work delves into the effect of vacancies and external electric fields on the electronic properties of the MSN/graphene(Gr)heterostructure using first-principles *** find that four types of defective structures,N-in,N-out,Si and Mo vacancy defects of monolayer MSN and MSN/Gr heterostructure are stable in ***,vacancy defects can effectively modulate the charge transfer at the interface of the MSN/Gr heterostructure as well as the work function of the pristine monolayer MSN and MSN/Gr ***,the application of an external electric field enables the dynamic switching between n-type and p-type Schottky *** work may offer the possibility of exceeding the capabilities of conventional Schottky diodes based on MSN/Gr heterostructures.

关键词： MoSi_(2)N_(4) vacancy defects external electric field Schottky contacts

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A robust tensor watermarking algorithm for diffusion-tensor images

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Frontiers of Information Technology & Electronic Engineering 2024年第3期25卷 384-397页

作者： Chengmeng LIU Zhi LI Guomei WANG Long ZHENG State Key Laboratory of Public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China

Watermarking algorithms that use convolution neural networks have exhibited good robustness in studies of deep learning ***,after embedding watermark signals by convolution,the feature fusion eficiency of convolution is relatively low;this can easily lead to distortion in the embedded *** distortion occurs in medical images,especially in diffusion tensor images(DTIs),the clinical value of the DTI is *** address this issue,a robust watermarking algorithm for DTIs implemented by fusing convolution with a Transformer is proposed to ensure the robustness of the watermark and the consistency of sampling distance,which enhances the quality of the reconstructed image of the watermarked DTIs after embedding the watermark *** the watermark-embedding network,Ti-weighted(Tlw)images are used as prior *** correlation between T1w images and the original DTI is proposed to calculate the most significant features from the T1w images by using the Transformer *** maximum of the correlation is used as the most significant feature weight to improve the quality of the reconstructed *** the watermark extraction network,the most significant watermark features from the watermarked DTI are adequately learned by the Transformer to robustly extract the watermark signals from the watermark *** results show that the average peak signal-to-noise ratio of the watermarked DTI reaches 50.47 dB,the diffusion characteristics such as mean diffusivity and fractional anisotropy remain unchanged,and the main axis deflection angleαAc is close to *** proposed algorithm can effectively protect the copyright of the DTI and barely affects the clinical diagnosis.

关键词： Robust watermarking algorithm Transformer Image reconstruction Diffusion tensor images Soft attention Hard attention Tl-weighted images

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Graphene effectively activating "dead" water molecules between manganese dioxide layers in potassium-ion battery

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Journal of Energy Chemistry 2024年第6期93卷 306-315,I0008页

作者： Xinhai Wang Wensheng Yang Shengshang Lu Shangshu Peng Tong Guo Quan Xie Qingquan Xiao Yunjun Ruan Institute of Advanced Optoelectronic Materials and Technology College of Big Data and Information EngineeringGuizhou UniversityGuiyang 550025GuizhouChina

Aqueous potassium-ion batteries(APIBs),recognized as safe and reliable new energy devices,are considered as one of the alternatives to traditional *** MnO_(2),serving as the main cathode,exhibits a lower specific capacity in aqueous electrolytes compared to organic systems and operates through a different reaction *** application of highly conductive graphene may effectively enhance the capacity of APIBs but could complicate the potassium storage *** this study,a MnO_(2) cathode pre-intercalated with K~+ions and grown on graphene(KMO@rGO) was developed using the microwave hydrothermal method for ***@rGO achieved a specific capacity of 90 mA h g^(-1) at a current density of 0.1 A g^(-1),maintaining a capacity retention rate of>90% after 5000 cycles at 5 A g^(-1).In-situ and exsitu characterization techniques revealed the energy-storage mechanism of KMO@rGO:layered MnO_(2)traps a large amount of "dead" water molecules during K~+ions ***,the introduction of graphene enables these water molecules to escape during K~+ ions insertion at the *** galvanostatic intermittent titration technique and density functional theory confirmed that KMO@rGO has a higher K~+ions migration rate than MnO_(2).Therefore,the capacity of this cathode depends on the interaction between dead water and K~+ions during the energy-storage *** optimal structural alignment between layered MnO_(2) and graphene allows electrons to easily flow into the external *** charge compensation forces numerous low-solvent K~+ions to displace interlayer dead water,enhancing the *** unique reaction mechanism is unprecedented in other aqueous battery studies.

关键词： Graphene K-ion batteries Mn-based layered oxide Water molecules Density functional theory

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Physical information-enhanced graph neural network for predicting phase separation

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Chinese Physics B 2024年第7期33卷 278-283页

作者：张亚强王煦文王雅楠郑文 Institute of Public-Safety and big data College of Computer Science and Technology(College of Data Science)Taiyuan University of TechnologyJinzhong 030600China Shanxi Engineering Research Centre for Intelligent data Assisted Treatment Changzhi Medical CollegeChangzhi 046000China Innovation Academy for Microsatellites of Chinese Academy of Sciences Shanghai 200050China

Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here,we present a physical information-enhanced graph neural network(PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt *** results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.

关键词： graph neural network phase separation machine learning dissipative particle dynamics

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Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers:A Life Course Perspective

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China CDC weekly 2024年第11期6卷 219-224,I0014-I0017页

作者： Cedric Zhang Bo Lua Yajie Gao Jinming Li Xingqi Cao Xinwei Lyu Yinuo Tu Shuyi Jin Zuyun Liu Center for Clinical big data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Healththe Key Laboratory of Intelligent Preventive Medicine of Zhejiang ProvinceZhejiang University School of MedicineHangzhou CityZhejiang ProvinceChina Institute of Epidemiology and Health Care University College LondonLondonUK college of Chemical and biological Engineering Zhejiang UniversityHangzhou CityZhejiang ProvinceChina

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of *** this study,we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English *** studies have predominantly used single biomarkers,such as C-reactive protein,or focused on specific life course stages and factors such as socioeconomic status,mental health,educational levels,and unhealthy *** summarizing the progress in this field,our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

关键词： such insight directions

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Unlocking high-efficiency oxygen evolution reaction through Co-N coordination engineering in Co@N-doped porous carbon core–shell nanoparticles

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Nano Research 2024年第8期17卷 7068-7076页

作者： Shucheng Liu Yu Shuai Xiaosi Qi Zhao Ding Yi Liu college of big data and Information Engineering Guizhou UniversityGuiyang 550025China college of Physics Guizhou Province Key Laboratory for Photoelectrics Technology and ApplicationGuizhou UniversityGuiyang 550025China

Modulation of metal sites coordination can significantly refine the electronic architecture of catalysts,thereby improving their catalytic *** work successfully developed a core–shell Co@N-doped porous carbon(Co@NC)catalyst by pyrolyzing the COF/MOF(IISERP-COF3/ZIF-67)composite in an inert *** Co@NC catalyst exhibited impressive oxygen evolution reaction(OER)performance,with a small overpotential of 304 mV and a modest Tafel slope of 88.6 mV·dec^(−1) in a 1 M KOH,alongside remarkable stability,maintaining 98.5%of its activity over 13 *** role of IISERP-COF3 was pivotal in preventing Co atom aggregation during the ZIF-67 pyrolysis,which facilitated the creation of mesopores for enhanced mass transport and ***,it effectively modulated the Co-N coordination to fine-tune the electronic structure,thereby optimizing the catalyst's capacity for adsorption of intermediates and boosting its intrinsic *** functional theory(DFT)studies corroborate that the exceptional OER efficiency of Co@NC can be linked to the enhanced Co-N coordination,optimizing the localized electronic structure at the Co active *** study not only proposes an innovative approach for optimizing COF/MOF as effective electrocatalysts but also clears the path for the emergence of affordable,high-performance alternatives to precious metal-based catalysts,marking a significant advancement in sustainable energy technologies.

关键词： covalent organic framework(COF) metal-organic framework(MOF) core-shell structure catalysts oxygen evolution reaction

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CAW-YOLO:Cross-Layer Fusion and Weighted Receptive Field-Based YOLO for Small Object Detection in Remote Sensing

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3209-3231页

作者： Weiya Shi Shaowen Zhang Shiqiang Zhang college of Artificial Intelligence and big data Henan University of TechnologyZhengzhou450001China college of Information Science and Engineering Henan University of TechnologyZhengzhou450001China

In recent years,there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural *** these efforts,the detection of small objects in remote sensing remains a formidable *** deep network structure will bring about the loss of object features,resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep ***,the features of small objects are susceptible to interference from background features contained within the image,leading to a decline in detection ***,the sensitivity of small objects to the bounding box perturbation further increases the detection *** this paper,we introduce a novel approach,Cross-Layer Fusion and Weighted Receptive Field-based YOLO(CAW-YOLO),specifically designed for small object detection in remote *** address feature loss in deep layers,we have devised a cross-layer attention fusion *** noise is effectively filtered through the incorporation of Bi-Level Routing Attention(BRA).To enhance the model’s capacity to perceive multi-scale objects,particularly small-scale objects,we introduce a weightedmulti-receptive field atrous spatial pyramid ***,wemitigate the sensitivity arising from bounding box perturbation by incorporating the joint Normalized Wasserstein Distance(NWD)and Efficient Intersection over Union(EIoU)*** efficacy of the proposedmodel in detecting small objects in remote sensing has been validated through experiments conducted on three publicly available *** experimental results unequivocally demonstrate the model’s pronounced advantages in small object detection for remote sensing,surpassing the performance of current mainstream models.

关键词： Small object detection attention mechanism cross-layer fusion discrete cosine transform

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Method for the classification of tea diseases via weighted sampling and hierarchical classification learning

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International Journal of Agricultural and biological Engineering 2024年第3期17卷 211-221页

作者： Rujia Li Weibo Qin Yiting He Yadong Li Rongbiao Ji Yehui Wu Jiaojiao Chen Jianping Yang college of big data Yunnan Agricultural UniversityKunming 650201China college of Plant Protection Jilin Agricultural UniversityChangchun 130118China

This study proposed a weighted sampling hierarchical classification learning method based on an efficient backbone network model to address the problems of high costs,low accuracy,and time-consuming traditional tea disease recognition *** method enhances the feature extraction ability by conducting hierarchical classification learning based on the EfficientNet model,effectively alleviating the impact of high similarity between tea diseases on the model’s classification *** better solve the problem of few and unevenly distributed tea disease samples,this study introduced a weighted sampling scheme to optimize data processing,which not only alleviates the overfitting effect caused by too few sample data but also balances the probability of extracting imbalanced classification *** experimental results show that the proposed method was significant in identifying both healthy tea leaves and four common leaf diseases of tea(tea algal spot disease,tea white spot disease,tea anthracnose disease,and tea leaf blight disease).After applying the“weighted sampling hierarchical classification learning method”to train 7 different efficient backbone networks,most of their accuracies have *** EfficientNet-B1 model proposed in this study achieved an accuracy rate of 99.21%after adopting this learning method,which is higher than EfficientNet-b2(98.82%)and MobileNet-V3(98.43%).In addition,to better apply the results of identifying tea diseases,this study developed a mini-program that operates on *** can quickly obtain accurate identification results and corresponding disease descriptions and prevention methods through simple *** intelligent tool for identifying tea diseases can serve as an auxiliary tool for farmers,consumers,and related scientific researchers and has certain practical value.

关键词： tea diseases hierarchical classification learning weighted sampling classification method EfficientNet miniprogram

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