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Machine learning for predicting the outcome of terminal ballistics events

Defence Technology（防务技术） 2024年第1期31卷 14-26页

作者： Shannon Ryan Neeraj Mohan Sushma Arun Kumar av.Julian Berk Tahrima Hashem Santu Rana Svetha Venkatesh Applied artificial intelligence Institute(A2I2) Deakin University75 Pigdons RdWaurn PondsVIC3216Australia

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal *** evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite *** achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release *** demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this *** extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is *** circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss *** physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is av.ilable and then revert to the physics-based model when *** resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical *** with numerical analysis tools such as finite element solvers the ML models run orders of magnitude *** provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballist

关键词： Machine learning artificial intelligence Physics-informed machine learning Terminal ballistics Armour

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Innovations in metallurgical and materials processes:advancing liquid theory and honoring ***-jie Guo's contributions to physical chemistry in metallurgy

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Journal of Iron and Steel Research(International) 2024年第1期31卷 1-2页

作者： Shuai Liu Jing Guo Han-jie Guo School of artificial intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology Beijing(USTB)Beijing100083China

Spanning three decades,***-jie Guo's research group has dedicated itself to exploring the fundamental theories and practical applications of physical chemistry within the realm of *** under the assumption that molecul... 详细信息

关键词： chemistry liquid complexes

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A Tutorial on Federated Learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use Cases,and Selected Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 824-850页

作者： M.Victoria Luzón Nuria Rodríguez-Barroso Alberto Argente-Garrido Daniel Jiménez-López Jose M.Moyano Jav.er Del Ser Weiping Ding Francisco Herrera Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Computer Science and artificial intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Communications Engineering University of the Basque Country(UPV/EHU)and also with TECNALIABasque Research&Technology Alliance(BRTA)Spain School of Information Science and Technology Nantong UniversityNantong 226019China

When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized *** allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third *** paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that hav. leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data *** virtue of FL,models can be learned from all such distributed data sources while preserving data *** aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software ***,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL *** ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.

关键词： Data privacy distributed machine learning federated learning software frameworks

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AI-Based Advanced Approaches and Dry Eye Disease Detection Based on Multi-Source Evidence:Cases,applications,Issues,and Future Directions

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Big Data Mining and Analytics 2024年第2期7卷 445-484页

作者： Mini Han Wang Lumin Xing Yi Pan Feng Gu Junbin Fang Xiangrong Yu Chi Pui Pang Kelvin Kam-Lung Chong Carol Yim-Lui Cheung Xulin Liao Xiaoxiao Fang Jie Yang Ruoyu Zhou Xiaoshu Zhou Fengling Wang Wenjian Liu Zhuhai People’s Hospital(Zhuhai Hospital Affiliated with Jinan University/The First Affiliated Hospital of Faculty of Medicine Macao University of Science and Technology) Zhuhai 519000China Department of Ophthalmology and Visual Sciences The Chinese University of Hong KongHong Kong 999077China Faculty of Data Science City University of MacaoMacao 999078China Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Zhuhai 519000China Perspective Technology group Zhuhai 519000China First Affiliated Hospital of Shandong First Medical University Shandong Provincial Qianfoshan Hospital Jinan 250000China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518000China College of Staten Island The City University of New YorkNY 10314USA Department of Optoelectronic Engineering Jinan UniversityGuangzhou 510000China Zhuhai Aier Eye Hospital Zhuhai 519000China College of artificial intelligence Chongqing Industry and Trade PolytechnicChongqing 400000China Centre for Science and Technology Exchange and Cooperation between China and Portuguese-Speaking Countries Zhuhai 519000China School of artificial intelligence Hezhou UniversityHezhou 542899China

This study explores the potential of artificial intelligence(AI)in early screening and prognosis of Dry Eye Disease(DED),aiming to enhance the accuracy of therapeutic approaches for eye-care *** the promising opportunities,challenges such as diverse diagnostic evidence,complex etiology,and interdisciplinary knowledge integration impede the interpretability,reliability,and applicability of AI-based DED detection *** research conducts a comprehensive review of datasets,diagnostic evidence,and standards,as well as advanced algorithms in AI-based DED detection over the past five *** DED diagnostic methods are categorized into three groups based on their relationship with AI techniques:(1)those with ground truth and/or comparable standards,(2)potential AI-based methods with significant advantages,and(3)supplementary methods for AI-based DED *** study proposes suggested DED detection standards,the combination of multiple diagnostic evidence,and future research directions to guide further ***,the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations,advanced methods,challenges,and potential future perspectives,emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.

关键词： artificial intelligence(AI) ophthalmology Dry Eye Disease(DED)detection multi-source evidence

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A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo groups and Neural Network

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 215-228页

作者： Shuyong Duan Jialin Zhang Heng Ouyang Xu Han Guirong Liu State Key Laboratory of Reliability and intelligence of Electrical Equipment Hebei University of TechnologyTianjin 300401China Department of Aerospace Engineering and Engineering Mechanics University of CincinnatiCincinnati 45221USA

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material *** work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material *** use of echo groups allows the use of lower frequencies,and hence more accommodative to structural *** train the ANNs,a numerical model is established that is capable of computing the wav.form of ultrasonic echo groups for any given set of material properties of a given *** wav.form of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical *** results in a set of dataset for training the ANN *** the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo wav.form as input to the *** tests hav. been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed *** results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic ***,the reliability and accuracy of inverse prediction is significantly ***,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other av.ilable methods or equipment.

关键词： Parameter identification Ultrasonic echo group High-precision modeling artificial neural network NDT

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A Reference Vector-Assisted Many-Objective Optimization Algorithm with Adaptive Niche Dominance Relation

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Intelligent Automation & Soft Computing 2024年第2期39卷 189-211页

作者： Fangzhen Ge Yating Wu Debao Chen Longfeng Shen School of Computer Science and Technology Huaibei Normal UniversityHuaibei340604China School of Physic and Electronic Information Huaibei Normal UniversityHuaibei340604China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behav.or(ICACB) Huaibei Normal UniversityHuaibei340604China Anhui Province Key Laboratory of Intelligent Computing and applications Huaibei Normal UniversityHuaibei340604China Institute of artificial intelligence Hefei Comprehensive National Science CenterHefei230000China

It is still a huge challenge for traditional Pareto-dominatedmany-objective optimization algorithms to solve manyobjective optimization problems because these algorithms hardly maintain the balance between convergence and diversity and can only find a group of solutions focused on a small area on the Pareto front,resulting in poor performance of those *** this reason,we propose a reference vector-assisted algorithmwith an adaptive niche dominance relation,for short *** new dominance relation forms a niche based on the angle between candidate *** comparing these solutions,the solutionwith the best convergence is found to be the non-dominated solution to improve the selection *** reproduction,a mutation strategy of k-bit crossover and hybrid mutation is used to generate high-quality *** 23 test problems with up to 15-objective,we compared the proposed algorithm with five state-of-the-art *** experimental results verified that the proposed algorithm is competitive.

关键词： Many-objective optimization evolutionary algorithm Pareto dominance reference vector adaptive niche

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Rectal Cancer Stages T2 and T3 Identification Based on Asymptotic Hybrid Feature Maps

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 923-938页

作者： Shujing Sun Jiale Wu Jian Yao Yang Cheng Xin Zhang Zhihua Lu Pengjiang Qian R&D Center of artificial intelligence Systems and applications School of Artificial Intelligence and Computer ScienceJiangnan UniversityWuxi214122China Shanghai Enterprise Information Operation Center China Telecom Group Co.Ltd.Shanghai201315China Department of Radiology Dushu Lake Hospital Affiliated to Soochow UniversitySuzhou215123China Suzhou Yunmai Software Technology Co. Ltd.Suzhou215100China

Many existing intelligent recognition technologies require huge datasets for model ***,it is not easy to collect rectal cancer images,so the performance is usually low with limited training *** addition,traditional rectal cancer staging is time-consuming,error-prone,and susceptible to physicians’subjective awareness as well as professional *** settle these deficiencies,we propose a novel deep-learning model to classify the rectal cancer stages of T2 and ***,a novel deep learning model(RectalNet)is constructed based on residual learning,which combines the squeeze-excitation with the asymptotic output layer and new cross-convolution layer links in the residual block ***,a two-stage data augmentation is designed to increase the number of images and reduce deep learning’s dependence on the volume of *** experiment results demonstrate that the proposed method is superior to many existing ones,with an overall accuracy of ***,other traditional techniques,such as VGG16,DenseNet121,EL,and DERNet,hav. an av.rage accuracy of 0.6981,0.7032,0.7500,and 0.7685,respectively.

关键词： Rectal cancer staging T2WI images data expansion asymptotic output layer

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Direct synthesis of unnatural amino acids and modifications of peptides via LADA strategy

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Chinese Chemical Letters 2024年第1期35卷 237-242页

作者： Yunqi Liu Junliang Zhou Zhankui Sun Shanghai Frontiers Science Center for Drug Target Identification and Drug Delivery School of Pharmaceutical SciencesShanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory for Molecular Engineering of Chiral Drugs Pharm-X CenterSchool of Pharmaceutical SciencesShanghai Jiao Tong UniversityShanghai 200240China AI Pharma Center Zhangjiang Institute for Advanced StudyShanghai Jiao Tong UniversityShanghai 201203China Shanghai artificial intelligence Laboratory Shanghai 200232China

Unnatural amino acids(UAAs)hav. broad applications in pharmaceutical sciences and biological *** synthetic methods for UAAs mainly rely on asymmetric catalysis and often require several *** is a lack of direct and simple *** address this challenge,we designed the LADA(labeling-activation-desulfurization-addition)strategy:selective labeling and activation of cysteine residues,the photocatalytic desulfurization and the subsequent radical addition to *** composed of two steps,it is one-pot synthesis and has advantages such as high functional group tolerance,biocompatible reaction condition,and retained *** highly efficient strategy was successfully applied in the direct synthesis of unnatural amino acids and modifications of peptides with more than 50 examples.

关键词： Unnatural amino acids Peptide modifications Desulfurization Cysteine Radical addition

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Noncooperative Model Predictive Game With Markov Jump Graph

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 931-944页

作者： Yang Xu Yuan Yuan Zhen Wang Xuelong Li School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Computer Science and Center for Optical Imagery Analysis and Learning Northwestern Polytechnical Universityand also with the School of CybersecurityNorthwestern Polytechnical UniversityXi’an 710072China School of artificial intelligence Optics and Electronics(iOPEN)Northwestern Polytechnical Universityand also with the Key Laboratory of Intelligent Interaction and ApplicationsNorthwestern Polytechnical UniversityMinistry of Industry and Information TechnologyXi’an 710072China

In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump *** reflect the reality,the state and input constraints hav. been considered along with the external *** iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed *** conditions are established to guarantee the convergence of the proposed *** addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying ***,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.

关键词： Markov jump graph model predictive control(MPC) multi-player systems(MPSs) noncooperative game ε-Nash equilibrium

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Detection of Partial Discharge in Power Transformers Using Rogowski Coil and Multiresolution Analysis

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Journal of Energy and Power Engineering 2010年第2期4卷 39-45页

作者： G.F.C. Veloso L.E. Borges da Silva I. Noronha G. Lambert Torres J. Haddad R.R. Pereira Se UnAhn group of artificial intelligence applications - unifei av. bps 1303 Pinheirinho - Itajuba MG CPFL Paulista Campinas Brasil

Partial discharge detection in power transformers is discussed using a new approach that exploit the broad band of the Rogowski coils and the potential of two signal processing tools: discrete wav.let transform and empirical mode decomposition. Detecting and analyzing incipient activities of partial discharge can provide useful information to diagnostics and prognostics about transformer insulation. So, partial discharge signals embedded in the electric current at ground conductor are measured using the Rogowski coil. These signals are submitted to noise suppression and the partial discharges wav.forms are extracted through different ways: using discrete wav.let transform and using empirical mode decomposition. The comparison of these two methods show that the extraction with discrete wav.let transform results in a faster and simpler algorithm than the empirical mode decomposition. But this one produces more precise wav.forms due its adaptive characteristic.

关键词： Rogowski线圈局部放电检测电力变压器多尺度分析经验模式分解离散小波变换局部放电信号信号处理

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