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Investigation on ignition characteristics of charring conductive polymers stimulated by electric energy

Chinese Journal of Aeronautics 2024年第10期37卷 68-82页

作者： Zhiyuan ZHANG Hanyu DENG Wenhe LIAO Yantao PU Ping CAO School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China Anhui Hongxing Electrical Polytron Technologies Inc. Hefei 231135China

The arc ignition based on charring conductive polymers has advantages of simple structure,low ignition power consumption and restart capacity,which bringing it broadly application prospect in hybrid propulsion system of micro/nano *** order to optimize the performance of arc ignition system,it is essential to have a deeper understanding of the ignition processes and ignition characteristics of charring conductive *** this paper,the thermal decomposition,electrical conductivity and thermal conductivity characteristics of charring conductive polymers with different conductive additives and matrix materials were comprehensively *** experimental investigation was conducted to determine the ignition behaviors and characteristics of different charring conductive polymers in a visual ignition *** experiment result showed that the ignition delay and external energy required for ignition are negatively correlated with voltage and initial temperature of the ignition grain,but positively correlated with oxidizer flow *** with charring conductive polymers containing multi-walled carbon nanotube,the ignition delay of charring conductive polymers with carbon black is significantly higher and the pyrolysis time is relatively ***,the ignition and initial flame propagation of charring conductive polymers with carbon black is more violent and more inclined to carbon particle ***,the restart characteristic of different charring conductive polymers was *** ignition delay and external energy required for ignition of different charring conductive polymers all reduced with the increasing of the number of ***,the ignition characteristics would not change a lot after repeated ignition.

关键词： Micro/nano satellite hybrid rocket motors Arc ignition Charring conductive polymer Ignition process Ignition characteristic Restart characteristic

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Cat Swarm Algorithm Generated Based on Genetic Programming Framework Applied in Digital Watermarking

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computers, Materials & Continua 2025年第5期83卷 3135-3163页

作者： Shu-Chuan Chu Libin Fu Jeng-Shyang Pan Xingsi Xue Min Liu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210000China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266000China Department of Information Management Chaoyang University of TechnologyTaichung40601TaiwanChina School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resource Nanjing University of Information Science and TechnologyNanjing210000China

Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.

关键词： Cat swarm algorithm genetic programming digital watermarking update mode mode generation framework

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Encapsulating perovskite quantum dots into 3D COF for visible light-driven CO_(2) reduction

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science China Chemistry 2025年第4期68卷 1478-1485页

作者： Xinxin Wang Yucheng Jin Xiya Yang Qingyu Luan Tianyu Wang Dongdong Qi Kang Wang Jianzhuang Jiang College of Chemistry and Materials Science Anhui Normal UniversityWuhu 241002China Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for Science and Application of Functional Molecular and Crystalline MaterialsDepartment of Chemistry and Chemical EngineeringSchool of Chemistry and Biological EngineeringUniversity of Science and Technology BeijingBeijing 100083China

Lead halide perovskite quantum dots(LHP QDs)have been revealed to possess great potential in photocatalytic applications including CO_(2)reduction;which however suffer from poor ***;a high crystalline hydrazine-linked three-dimensional(3D)covalent organic framework;USTB-17;was fabricated from the reaction between 12-connected building block and 4-connected 3,5,7-tetrakis(4-aldophenyl)-***-modification with Ni^(2+) affords the metallic framework USTB-17(Ni)followed by sequential deposition of the CH_(3)NH_(2)PbI_(3)(MAPbI_(3))perovskite QDs into its pores;generating the USTB-17(Ni)@MAPbI_(3) *** X-ray diffraction analysis together with theoretical simulations and transmission electron microscopy discloses the crystalline nature of USTB-17;USTB-17(Ni);and USTB-17(Ni)@MAPbI_(3) with an unprecedented noninterpenetrated hpt *** close contact of QDs inside the COF pores with the Ni catalytic site locating at the pore surface of COF allows a rapid transfer of the photogenerated electrons in QDs to the Ni catalytic sites;enhancing the photocatalytic activity for CO_(2)*** endows USTB-17(Ni)@MAPbI_(3) with efficient photocatalysis performance for photocatalytic CO_(2)reduction with CO generation rate of 365μmol g^(-1)h^(-1)and CO selectivity up to 96%under visible-light irradiation;7 times higher than that of USTB-17(Ni).After four cycles of reactions;the photocatalytic CO generation rate remains almost unchanged;demonstrating its excellent cycle stability.

关键词： lead halide perovskite quantum dots 3D covalent organic frameworks hpt topology photocatalytic CO_(2)reduction

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An Improved Hybrid Deep Learning Approach for Security Requirements Classification

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computers, Materials & Continua 2025年第3期82卷 4041-4067页

作者： Shoaib Hassan QianmuLi Muhammad Zubair Rakan AAlsowail Muhammad Umair School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China Faculty of Information Technology and Computer Science University of Central PunjabLahore5400Pakistan Computer Skills Self-Development Skills DevelopmentDeanship of Common First YearKing Saud UniversityRiyadh11362Saudia Arabia

As the trend to use the latestmachine learning models to automate requirements engineering processes continues,security requirements classification is tuning into the most researched field in the software engineering *** literature studies have proposed numerousmodels for the classification of security ***,adopting those models is constrained due to the lack of essential datasets permitting the repetition and generalization of studies employing more advanced machine learning ***,most of the researchers focus only on the classification of requirements with security *** did not consider other nonfunctional requirements(NFR)directly or indirectly related to *** has been identified as a significant research gap in security requirements *** major objective of this study is to propose a security requirements classification model that categorizes security and other relevant security *** use PROMISE_exp and DOSSPRE,the two most commonly used datasets in the software engineering *** proposed methodology consists of two *** the first step,we analyze all the nonfunctional requirements and their relation with security *** found 10 NFRs that have a strong relationship with security *** the second step,we categorize those NFRs in the security requirements *** proposedmethodology is a hybridmodel based on the ConvolutionalNeural Network(CNN)and Extreme Gradient Boosting(XGBoost)***,we evaluate the model by updating the requirement type column with a binary classification column in the dataset to classify the requirements into security and non-security *** performance is evaluated using four metrics:recall,precision,accuracy,and F1 Score with 20 and 28 epochs number and batch size of 32 for PROMISE_exp and DOSSPRE datasets and achieved 87.3%and 85.3%accuracy,*** proposed study shows an enhancement in metrics

关键词： Requirements engineering security requirements deep learning CNN XGBoost classification

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Constructing a stable interface on Ni-rich LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) cathode via lactic acid-assisted engineering strategy

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Journal of Energy Chemistry 2024年第3期90卷 412-422,I0010页

作者： Weijian Tang Chengzhi Hu AFei Li Xiaoqin Huang Zhangxian Chen Jianhui Su Weixin Zhang Institute of Energy Hefei Comprehensive National Science CenterHefei 230031AnhuiChina School of Chemistry and Chemical Engineering Hefei University of Technology and Anhui Key Laboratory of Controllable Chemical Reaction&Material Chemical EngineeringHefei 230009AnhuiChina School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009AnhuiChina

Ni-rich layered oxides are potential cathode materials for next-generation high energy density Li-ion batteries due to their high capacity and low ***,the inherently unstable surface properties,including high levels of residual Li compounds,dissolution of transition metal cations,and parasitic side reactions,have not been effectively addressed,leading to significant degradation in their electrochemical *** this study,we propose a simple and effective lactic acid-assisted interface engineering strategy to regulate the surface chemistry and properties of Ni-rich LiNi_(0.8)Co_(0.1)Mr_(0.1)O_(2) *** novel surface treatment method successfully eliminates surface residual Li compounds,inhibits structural collapse,and mitigates cathode-electrolyte interface film *** a result,the lactic acidtreated LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) achieved a remarkable capacity retention of 91.7% after 100 cycles at 0.5 C(25℃) and outstanding rate capability of 149.5 mA h g^(-1) at 10 C,significantly outperforming the pristine ***,a pouch-type full cell incorporating the modified LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) cathode demonstrates impressive long-term cycle life,retaining 81.5% of its capacity after 500 cycles at 1 *** importantly,the thermal stability of the modified cathode is also dramatically *** study offers a valuable surface modification strategy for enhancing the overall performance of Ni-rich cathode materials.

关键词： Residual Li Lactic acid Surface modification Carbon coating Layered cathode Ni-rich

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Stress Distribution Characteristics and Energy Evolution Law of Drilling Pressure Relief 43

Stress Distribution Characteristics and Energy Evolution Law...

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43rd International Conference on Ground Control in Mining, ICGCM 2024, held at the 2024 SME Annual Conference and Expo

作者： Zhang, Kai Li, Yingming Chi, Xiaolou Yang, Ke Zhang, Xiangyang School of Mining Engineering Anhui University of Science and Technology China

ISBN: (纸本)9798331300487

Based on the research background of 1303 working face return air roadway in Jinyuan Zhaoxian Mine, Shaanxi Province, a method of determining the reasonable spacing of boreholes is proposed based on the stress transfer degree of coal above and between boreholes, combined with the law of plastic zone and energy evolution by theoretical analysis and numerical simulation. After drilling pressure relief, the average daily energy of microseismic events decreased by 70%, and those with microseismic energy greater than 104 J decreased by 99.2%. The research has a strong guiding significance and research value for determining the reasonable distance of borehole pressure relief. © ICGCM 2024 . All rights reserved.

关键词： Boreholes

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Improved Set Algebra-Based Heuristic Technique for Training Multiplicative Functional Link Artificial Neural Networks for Financial Time Series Forecasting

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SN computer science 2024年第5期5卷 1-34页

作者： Behera, Sudersan Kumar, AVS Pavan Nayak, Sarat Chandra Department of Computer Science and Engineering School of Engineering & amp Technology GIET University Gunupur India Department of Computer Science and Engineering School of Technology GITAM University Hyderabad India

The current study is defined by two main aims. An effective strategy for improving local search is to combine the Set Algebra-Based Heuristic Algorithm (SAHA) algorithm with the Nelder-Mead simplex method. The approach outlined above, referred to as the Improved SAHA (ISAHA), and has the ability to produce superior outcomes. The multiplicative functional link artificial neural network (MFLANN) is an improved version of the functional link artificial neural network that promotes exploration by replacing the summing unit in the output layer with a multiplication unit. Moreover, the combination of ISAHA and MFLANN results in the development of ISAHA-MFLANN, a sophisticated hybrid forecasting model. The main assessment of the hybrid model rests on its ability to forecast complex and dynamic financial time series. It's possible to get around the problems that come with traditional learning-based MFLANN techniques by using MFLANN's advanced approximation features and ISAHA's resilient global search features together. Experimental verification using two stock market datasets and three currency exchange rates demonstrates the validity of the idea. The results show that the suggested improved SAHA hybrid learning works well at improving six standard benchmark functions. The ISAHA-MFLANN model is also statistically significant at accurately capturing the volatility that is inherent in the financial time series. In addition, it surpasses other models such as SAHA-MFLANN, Monarch Butterfly Optimization-MFLANN, Particle Swarm Optimization-MFLANN, Genetic Algorithm-MFLANN, Gradient Descent-MFLANN, Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Auto Regressive Integrated Moving Average (ARIMA). © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Exchange rate forecasting Improved Set Algebra-Based Heuristic Algorithm Multiplicative functional link artificial neural network Stock market forecasting

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DAFPN-YOLO: An Improved UAV-Based Object Detection Algorithm Based on YOLOv8s

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computers, Materials & Continua 2025年第5期83卷 1929-1949页

作者： Honglin Wang Yaolong Zhang Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Electrical&Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA

UAV-based object detection is rapidly expanding in both civilian and military applications,including security surveillance,disaster assessment,and border ***,challenges such as small objects,occlusions,complex backgrounds,and variable lighting persist due to the unique perspective of UAV *** address these issues,this paper introduces DAFPN-YOLO,an innovative model based on YOLOv8s(You Only Look Once version 8s).Themodel strikes a balance between detection accuracy and speed while reducing parameters,making itwell-suited for multi-object detection tasks from drone perspectives.A key feature of DAFPN-YOLO is the enhanced Drone-AFPN(Adaptive Feature Pyramid Network),which adaptively fuses multi-scale features to optimize feature extraction and enhance spatial and small-object *** leverage Drone-AFPN’smulti-scale capabilities fully,a dedicated 160×160 small-object detection head was added,significantly boosting detection accuracy for small *** the backbone,the C2f_Dual(Cross Stage Partial with Cross-Stage Feature Fusion Dual)module and SPPELAN(Spatial Pyramid Pooling with Enhanced LocalAttentionNetwork)modulewere *** components improve feature extraction and information aggregationwhile reducing parameters and computational complexity,enhancing inference ***,Shape-IoU(Shape Intersection over Union)is used as the loss function for bounding box regression,enabling more precise shape-based object *** results on the VisDrone 2019 dataset demonstrate the effectiveness *** to YOLOv8s,the proposedmodel achieves a 5.4 percentage point increase inmAP@0.5,a 3.8 percentage point improvement in mAP@0.5:0.95,and a 17.2%reduction in parameter *** results highlight DAFPN-YOLO’s advantages in UAV-based object detection,offering valuable insights for applying deep learning to UAV-specific multi-object detection tasks.

关键词： YOLOv8 UAV-based object detection AFPN small-object detection head SPPELAN DualConv loss function

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Microstructure Characteristics and Elevated Temperature Mechanical Properties of a B Containedβ-solidifiedγ-TiAl Alloy

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Journal of Wuhan university of technology(Materials science) 2024年第3期39卷 738-746页

作者：王秀琦 GUO Ruiqi 刘国怀 LI Tianrui YANG Yuxuan CHEN Yang XIN Meiling WANG Zhaodong State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang 110819China School of Materials Science and Engineering Harbin Institute of Technology at ShenzhenShenzhen 518055China School of Metallurgical Engineering Anhui University of TechnologyMaanshan 243000China

The improved microstructure and enhanced elevated temperature mechanical properties of Ti-44Al-5Nb-(Mo,V,B)alloys were obtained by vacuum arc re-melting(VAR)and primary annealing heat treatment(HT)of 1260℃/6 h/Furnace cooling(FC).The phase transformation,microstructure evolution and tensile properties for as-cast and HTed alloys were *** indicate that three main phase transformation points are determined,T_(eut)=1164.3℃,T_(γsolv)=1268.3℃and T_(βtrans)=1382.8℃.There are coarse lamellar colonies(300μm in length)and neighbor reticular B2 andγgrain(3-5μm)in as-cast alloy,while lamellar colonies are markedly refined and multi-oriented(20-50μm)as well as the volume fraction and grain sizes of equiaxedγand B2 phases(about 15μm)significantly increase in as-HTed *** transformations involvingα+γ→α+γ+β/B2 and discontinuousγcoarsening contribute to the above ***(1-3μm)act as nucleation sites forβ_(eutectic) and produce massiveβgrains with different orientations,thus effectively refining the lamellar colonies and forming homogeneous multi-phase *** curves show both the alloys exhibit suitable performance at 800℃.As-cast alloy shows a higher ultimate tensile stress of 647 MPa,while a better total elongation of more than 41%is obtained for as-HTed *** mechanical properties improvement is mainly attributed to fine,multi-oriented lamellar colonies,coordinated deformation of homogeneous multi-phase microstructure and borides within lamellar interface preventing crack propagation.

关键词： TiAl alloy phase transformation heat treatment boride microstructure mechanical properties

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Ontology-Based Semantic Reasoning for Multi-Source Heterogeneous Industrial Devices Using OPC UA

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IEEE Internet of Things Journal 2025年第13期12卷 25020-25032页

作者： Bi, Jing Wu, Rina Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu Beijing University of Technology College of Computer Science Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing China Southern Methodist University Department of Computer Science Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

The advent of smart manufacturing in Industry 4.0 signifies the era of connections. As a communication protocol, Object linking and embedding for Process Control Unified Architecture (OPC UA) can address most semantic heterogeneity issues. However, its semantics are not formally defined at the application layer. To address the information silo problem caused by semantic heterogeneity, an integration framework named Querying of Ontology Mapping-based OPC UA (QOMOU) is proposed. QOMOU extracts information models of OPC UA servers into resource description framework triples and utilizes web ontology language for semantic enrichment and inference. Then, an Event Class Semantic Similarity Calculation (ECSSC) method is proposed for device type identification, enabling the classification of semantically heterogeneous OPC UA devices. The effectiveness of ECSSC is validated through queries with the RDF query language (SPARQL) protocol in Apache Jena. Experimental results demonstrate that ECSSC improves the accuracy of device identification by approximately 7% compared to benchmark device identification models. Specifically, compared with graph embedding-based methods, QOMOU’s query performance is approximately 13% higher, and its query efficiency is 5% higher on average compared to both structured query and extensible markup languages. Moreover, by employing a keyword-matching algorithm, the query accuracy of the existing heterogeneous data integration scheme is improved by 4% on average. This enhancement can boost the operational efficiency of Internet of Things systems based on the OPC UA architecture. © 2014 IEEE.

关键词： Structured Query Language

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