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Multi-party privacy-preserving decision tree training with a privileged party

Science China(Information Sciences) 2024年第8期67卷 253-268页

作者： Yiwen TONG Qi FENG Min luo Debiao HE Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Matrix Elements Technologies Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center Qilu University of Technology(Shandong Academy of Sciences)

Currently, a decision tree is the most commonly used data mining algorithm for classification tasks. While a significant number of studies have investigated privacy-preserving decision trees, the methods proposed in these studies often have shortcomings in terms of data privacy breach or efficiency. Additionally,these methods typically only apply to symmetric frameworks, which consist of two or more parties with equal privilege, and are not suitable for asymmetric scenarios where parties have unequal privilege. In this paper,we propose SecureCART, a three-party privacy-preserving decision tree training scheme with a privileged party. We adopt the existing pMPL framework and design novel secure interactive protocols for division,comparison, and asymmetric multiplication. Compared to similar schemes, our division protocol is 93.5–560.4× faster, with the communication overhead reduced by over 90%; further, our multiplication protocol is approximately 1.5× faster, with the communication overhead reduced by around 20%. Our comparison protocol based on function secret sharing maintains good performance when adapted to pMPL. Based on the proposed secure protocols, we implement SecureCART in C++ and analyze its performance using three real-world datasets in both LAN and WAN environments. he experimental results indicate that SecureCART is significantly faster than similar schemes proposed in past studies, and that the loss of accuracy while using SecureCART remains within an acceptable range.

关键词： privacy protection decision trees secure multi-party computation secret sharing privileged party

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Inversely engineered metasurfaces for independent manipulation of transmitted and reflected light fields

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Science China(Physics,Mechanics & Astronomy) 2024年第7期67卷 97-106页

作者： Yongjian Liu Yu luo Fei Zhang Mingbo Pu Hanlin Bao Mingfeng Xu Yinghui Guo Lanting Li Xiong Li Xiaoliang Ma Xiangang luo National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of SciencesChengdu 610209China State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering Institute of Optics and ElectronicsChinese Academy of SciencesChengdu 610209China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of SciencesBeijing 100049China Research Center on Vector Optical Fields Institute of Optics and ElectronicsChinese Academy of SciencesChengdu 610209China Tianfu Xinglong Lake Laboratory Chengdu 610299China

Independent manipulation of transmitted and reflected light fields is a key technology for the realization of multifunctional optical applications,which can be implemented based on multilayered plasmonic or supercell subwavelength ***,the former is not suitable for the optical bands,while the latter is insufficient in generating large phase ***,an adjoint-optimization-based inverse design methodology is proposed,which utilizes the polarization-selective local interference between individual meta-atoms and enables monolayer dielectric metasurfaces to decouple the wavefront of transmitted and reflected optical ***,this methodology serves to mitigate the aperiodic electromagnetic crosstalk inherent between adjacent meta-atoms,consequently leading to a significant enhancement in the performance of *** analyzed the physical mechanism of adjoint optimization and proposed the concept of phase factors,highlighting their importance in the rapid inverse design of meta-devices—an aspect often overlooked in previous *** demonstrate the feasibility and robustness of our method,we optimize monolayer metasurfaces with different initial *** devices efficiently focus and deflect x-linearly and y-linearly polarized incident light in transmission and reflection spaces,***,this methodology holds immense potential for designing multifunctional,high-performing metasurfaces that meet multiple constraints,opening up broad prospects for applications.

关键词： full-space metasurfaces adjoint optimization inverse design

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Sponge as Scaffolds in Bone and Cartilage Tissue Engineering

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CHEMICAL RESEARCH IN CHINESE UNIVERSITIES 2024年第5期40卷 786-797页

作者： luo, Lei Gong, Yining Yan, Liang Bu, Yazhong Yanan Univ Yanan 716000 Peoples R China Xi An Jiao Tong Univ Honghui Hosp Dept Spine Surg Xian 710054 Peoples R China Xi An Jiao Tong Univ Inst Med Engn Hlth Sci Ctr Sch Basic Med SciDept Biophys Xian 710061 Peoples R China

In recent years, tissue scaffolds have emerged as a new therapeutic method for bone and cartilage regeneration, with sponge scaffolds gaining increasing attention. Sponge scaffolds possess several favorable characteristics, including appropriate biodegradability, excellent biocompatibility, good processability, powerful osteogenic ability, a unique porous structure, and adjustable pore size and connectivity. These attributes make sponge scaffolds a promising option for bone and cartilage regeneration. However, to date, there is a lack of comprehensive reviews summarizing the use of sponge scaffolds in this field. In this review, our objective is to provide a comprehensive overview of the research progress and development trends of sponge scaffolds. Firstly, we introduce the various materials used for sponge scaffolds. Secondly, we summarize the different preparation methods employed for creating sponge scaffolds. Subsequently, we discuss the functional additives that can be incorporated into the scaffolds. Finally, we present some special structures that can be achieved in sponge scaffolds. Our aim is for this review to offer valuable insights and serve as a comprehensive resource for the design of sponge scaffolds in cartilage and bone regeneration.

关键词： Bone Sponge Scaffold Tissue regeneration COMPOSITE SCAFFOLDS REGENERATIVE MEDICINE STEM-CELLS FABRICATION IRISIN VIVO DIFFERENTIATION PHYSIOLOGY STRATEGIES MENISCUS

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Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3147-3165页

作者： Yifan Huang Zikang Zhou Mingyu Li Xuedong luo Faculty of Engineering China University of GeosciencesWuhan430074China Institute of Geological Survey China University of GeosciencesWuhan430074China

Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration *** this study,Tuna Swarm Optimization(TSO),Whale Optimization Algorithm(WOA),and Cuckoo Search(CS)were used to optimize two hyperparameters in support vector regression(SVR).Based on these methods,three hybrid models to predict peak particle velocity(PPV)for bench blasting were ***-eight samples were collected to establish the PPV database,eight initial blasting parameters were chosen as input parameters for the predictionmodel,and the PPV was the output *** predictive performance evaluation indicators,the coefficient of determination(R2),rootmean square error(RMSE),mean absolute error(MAE),and a10-index were *** normalizedmutual information value is then used to evaluate the impact of various input parameters on the PPV prediction *** to the research findings,TSO,WOA,and CS can all enhance the predictive performance of the SVR *** TSO-SVR model provides the most accurate *** performances of the optimized hybrid SVR models are superior to the unoptimized traditional prediction *** maximum charge per delay impacts the PPV prediction value the most.

关键词： Blasting vibration metaheuristic algorithms support vector regression peak particle velocity normalized mutual information

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A Survey of Knowledge Graph Construction Using Machine Learning

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 225-257页

作者： Zhigang Zhao Xiong luo Maojian Chen Ling Ma School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFoshan528399China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured *** framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity *** this transformative process,the advancement of artificial intelligence and intelligent information services is ***,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial *** article embarks on a comprehensive journey through the last strides in the field of KG via machine *** a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge ***,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link ***,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.

关键词： Knowledge graph(KG) semantic network relation extraction entity linking knowledge reasoning

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Dynamic Multi-Physics Behaviors and Performance Loss of Cylindrical Batteries Upon Low-Velocity Impact Loading

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ENERGY & ENVIRONMENTAL MATERIALS 2024年第6期7卷 184-192页

作者： Huang, Qingdan Bai, Yang luo, Han Jia, Yikai Zhang, Chao Northwestern Polytech Univ Sch Civil Aviat Xian 710072 Peoples R China Key Lab Impact Protect & Safety Assessment Civil A Taicang 215400 Peoples R China Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China EVE Energy Co Ltd Huizhou 516006 Peoples R China

In challenging operational environments, Lithium-ion batteries (LIBs) inevitably experience mechanical stresses, including impacts and extrusion, which can lead to battery damage, failure, and even the occurrence of fire and explosion incidents. Consequently, it is imperative to investigate the safety performance of LIBs under mechanical loads. This study is grounded in a more realistic coupling scenario consisting of electrochemical cycling and low-velocity impact. We systematically and experimentally uncovered the mechanical, electrochemical, and thermal responses, damage behavior, and corresponding mechanisms under various conditions. Our study demonstrates that higher impact energy results in increased structural stiffness, maximum temperature, and maximum voltage drop. Furthermore, heightened impact energy significantly influences the electrical resistance parameters within the internal resistance. We also examined the effects of State of Charge (SOC) and C-rates. The methodology and experimental findings will offer insights for enhancing the safety design, conducting risk assessments, and enabling the cascading utilization of energy storage systems based on LIBs. In this study, the impact of low-velocity impacts on the performance and safety of LIBs is explored. Various conditions, such as impact energy, State of Charge (SOC), and C-rates, systematically reveal mechanical, electrochemical, and thermal responses, as well as damage behaviors. The study demonstrates that higher energy leads to increased structural stiffness, maximum temperature, and maximum voltage drop. Additionally, heightened impact energy and SOC significantly influence electrochemical parameters, including charging capacity and internal resistance. image

关键词： cycling performance damaged battery lithium-ion battery low-velocity impact mechanical safety LITHIUM-ION BATTERY SHORT-CIRCUIT MECHANICAL-BEHAVIOR POUCH CELLS COMPUTATIONAL MODEL ELECTRIC VEHICLES THERMAL-BEHAVIOR STRAIN-RATE DEFORMATION OVERCHARGE

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Shape optimisation of basin insulator for DC gas insulated switchgear/gas insulated transmission lines based on artificial bee colony algorithm

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High Voltage 2024年第2期9卷 275-286页

作者： Yi luo Shiyi Mao Ju Tang Zijun Pan Cheng Pan State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhanChina

The surface charge accumulation on the basin insulator is a particular problem in high-voltage direct current(HVDC)gas insulated switchgears(GIS)and gas insulated trans-mission lines(GIL),which restricts the development and application of extra/ultra high-voltage(EHV/UHV)*** surface charge distribution and anti-flashover performance are closely related to the insulator *** obtain the optimal basin insulator,a shape optimisation model based on artificial bee colony algorithm was established,and the minimisation objective functions based on capacitive(initial)electric field distribution and resistive(steady-state)electric field distribution were respectively *** optimisation results of the two objective functions were calculated,and the electric field and charge distribution on the surface of the insulator before and after optimisation were evaluated and compared using the simulation *** results indicated that the optimisation based on the capacitive electric field can significantly inhibit the surface charge accumulation,and the optimised insulator can significantly reduce the surface normal electric field and make the distribution of the tangential electric field more uniform,and the maximum tangential electric field can be reduced by 10%;the optimisation based on resistive electric field can achieve similar results,but requires more computational *** on the results,the‘anti-charge’basin insulator structure suitable for the DC field was given.

关键词： insulator artificial charge

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A Novel 3D Gait Model for Subject Identification Robust against Carrying and Dressing Variations

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Computers, Materials & Continua 2024年第7期80卷 235-261页

作者： Jian luo Bo Xu Tardi Tjahjadi Jian Yi College of Information Science and Engineering Hunan Normal UniversityChangsha410000China School of Engineering University of WarwickCoventryCV47ALUK

Subject identification via the subject’s gait is challenging due to variations in the subject’s carrying and dressing conditions in real-life *** paper proposes a novel targeted 3-dimensional(3D)gait model(3DGait)represented by a set of interpretable 3DGait descriptors based on a 3D parametric body *** 3DGait descriptors are utilised as invariant gait features in the 3DGait recognition method to address object carrying and *** 3DGait recognitionmethod involves 2-dimensional(2D)to 3DGaitdata learningbasedon3Dvirtual samples,a semantic gait parameter estimation Long Short Time Memory(LSTM)network(3D-SGPE-LSTM),a feature fusion deep model based on a multi-set canonical correlation analysis,and SoftMax recognition ***,a sensory experiment based on 3D body shape and pose deformation with 3D virtual dressing is used to fit 3DGait onto the given 2D gait images.3Dinterpretable semantic parameters control the 3D morphing and dressing *** degree measurement determines the semantic descriptors of 2D gait images of subjects with various shapes,poses and ***,using the 2D gait images as input and the subjects’corresponding 3D semantic descriptors as output,an end-to-end 3D-SGPE-LSTM is constructed and ***,body shape,pose and external gait factors(3D-eFactors)are estimated using the 3D-SGPE-LSTM model to create a set of interpretable gait descriptors to represent the 3DGait Model,i.e.,3D intrinsic semantic shape descriptor(3DShape);3D skeleton-based gait pose descriptor(3D-Pose)and 3D dressing with other ***,the 3D-Shape and 3D-Pose descriptors are coupled to a unified pattern space by learning prior knowledge from the *** research on CASIA B,CMU MoBo,TUM GAID and GPJATK databases shows that 3DGait is robust against object carrying and dressing variations,especially under multi-cross variations.

关键词： Gait recognition human identification three-dimensional gait canonical correlation analysis

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Uniaxial Compressive Strength Prediction for Rock Material in Deep Mine Using Boosting-Based Machine Learning Methods and Optimization Algorithms

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 275-304页

作者： Junjie Zhao Diyuan Li Jingtai Jiang Pingkuang luo School of Resources and Safety Engineering Central South UniversityChangsha410083China

Traditional laboratory tests for measuring rock uniaxial compressive strength(UCS)are tedious and *** is a pressing need for more effective methods to determine rock UCS,especially in deep mining environments under high in-situ ***,this study aims to develop an advanced model for predicting the UCS of rockmaterial in deepmining environments by combining three boosting-basedmachine learning methods with four optimization *** this purpose,the Lead-Zinc mine in Southwest China is considered as the case *** density,P-wave velocity,and point load strength index are used as input variables,and UCS is regarded as the ***,twelve hybrid predictive models are *** mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R2),and the proportion of the mean absolute percentage error less than 20%(A-20)are selected as the evaluation *** results showed that the hybridmodel consisting of the extreme gradient boostingmethod and the artificial bee colony algorithm(XGBoost-ABC)achieved satisfactory results on the training dataset and exhibited the best generalization performance on the testing *** values of R2,A-20,RMSE,and MAE on the training dataset are 0.98,1.0,3.11 MPa,and 2.23MPa,*** highest values of R2 and A-20(0.93 and 0.96),and the smallest RMSE and MAE values of 4.78 MPa and 3.76MPa,are observed on the testing *** proposed hybrid model can be considered a reliable and effective method for predicting rock UCS in deep mines.

关键词： Uniaxial compression strength strength prediction machine learning optimization algorithm

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Rapid chemical recycling of waste polyester plastics catalyzed by recyclable catalyst

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Green Chemical Engineering 2024年第2期5卷 257-265页

作者： Yu-Ji luo Jia-Yin Sun Zhi Li School of Physical Science and Technology ShanghaiTech UniversityShanghai201210China

Waste plastics are serious environmental threats due to their low degradability and low recycling *** and efficient waste plastics recycling technologies are urgently demanded for a sustainable ***,we report a rapid,closed-loop,and streamlined process to convert polyesters such as poly(ethylene terephthalate)(PET)back to its purified *** trifluoromethanesulfonic acid or metal triflates as the recyclable catalyst,polyesters such as PET can be completely depolymerized by simple carboxylic acids within 1 *** coupling this acidolysis with a subsequent hydrogenolysis process,the consumed carboxylic acid was recovered and the closed-loop of PET depolymerization could be *** catalysts and depolymerization agents are fully recycled while only PET and hydrogen are consumed.

关键词： Chemical recycling Waste polyester plastics Acidolysis Recyclable catalyst

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