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A facile high-efficiency preparation strategy for Al-containing multi-component boride microcrystals with superior comprehensive performance

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Journal of Materials science & technology 2025年第1期204卷 190-203页

作者： Yong Fan Jinfeng Nie Zhigang Ding Yujing Zhang Xiang Chen Wei Liu Sen Yang Sida Liu Xiangfa Liu Yonghao Zhao Nano and Heterogeneous Materials Center School of Materials Science and EngineeringNanjing University of Science and TechnologyNanjing 210094China School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Laboratory for multiscale mechanics and medical science SV LABSchool of AerospaceXi’an Jiaotong UniversityXi’an 710049China Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationShandong UniversityJinan 250061China School of Materials Science and Engineering Hohai UniversityChangzhou 213200China

Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional *** of the current methods,however,are complicated and time-consuming,the mass production remains a ***,we proposed a new high-efficiency strategy for synthesis of MMB_(2)using molten aluminum as the medium for the first *** prepared Al-containing multi-component borides(TiZrHfNbTa)B_(2)microcrystals had a homogeneous composition with a hexagonal AlB_(2)structure and ultra-high hardness value of∼35.3 GPa,which was much higher than data reported in the literature and the rule of mix-ture ***,combined with the First-principles calculation results,we found that the Poisson’s ratio(v)values exhibit a clearly ascending trend from 0.17 at VEC=3.5 to 0.18 at VEC=3.4,then to 0.201 at VEC=3.2 with the increasing of Al *** indicates that the intrinsic toughness of multi-component boride microcrystals is obviously enhanced by the trace-doped Al ***,the fabricated Al-containing multi-component boride microcrystals have superior oxidation activation en-ergy and structural *** enhanced oxidation resistance is mainly attributed to the formation of a protective Al2 O3 oxide layer and the lattice distortion,both of which lead to sluggish diffusion of O_(2).These findings propose a new unexplored avenue for the fabrication of MMB_(2)materials with supe-rior comprehensive performance including ultra-hardness and intrinsically improved thermo-mechanical properties.

关键词： Multi-component borides First-principles calculations Crystal growth Mechanical properties Oxidation behavior

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Cross-Language Dependencies: An Empirical Study of Kotlin-Java 24

Cross-Language Dependencies: An Empirical Study of Kotlin-Ja...

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18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2024

作者： Feng, Qiong Ji, Huan Ma, Xiaotian Liang, Peng School of Computer Science Nanjing University of Science and Technology Nanjing China School of Computer Science Wuhan University Wuhan China

ISBN: (纸本)9798400710476

Background: Since Google introduced Kotlin as an official programming language for developing Android apps in 2017, Kotlin has gained widespread adoption in Android development. The interoperability of Java and Kotlin's design nature allows them to coexist and interact with each other smoothly within a project. Aims: However, there is limited research on how Java and Kotlin interact with each other in real-world projects and what challenges are faced during these interactions. The answers to these questions are key to understanding these kinds of cross-language software systems. Methods: In this paper, we implemented a tool named DependExtractor, which can extract 11 kinds of Kotlin-Java dependencies, and conducted an empirical study of 23 Kotlin-Java real-world projects with 3,227 Java and 8,630 Kotlin source files. Results: Our findings revealed that Java and Kotlin frequently interact with each other in these cross-language projects, with access and call dependency types being the most dominant. Compared to files interacting with other files in the same language, Java/Kotlin source files, which participate in the cross-language interactions, undergo more commits. Additionally, among all Kotlin-Java problematic interactions, we identified seven common mistakes, along with their fixing strategies. Conclusions: The findings of this study can help developers understand and address the challenges in Kotlin-Java projects. © 2024 ACM.

关键词： Code Dependency

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Resource investment for DDoS attack resistant SDN: a practical assessment

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science China(Information sciences) 2023年第7期66卷 112-129页

作者： Bin YUAN Fan ZHANG Jun WAN Huan ZHAO Shui YU Deqing ZOU Qiangsheng HUA Hai JIN School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Shenzhen Huazhong University of Science and Technology Research Institute School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab School of Computer Science University of Technology Sydney

Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.

关键词： SDN security DDoS attacks resource management queueing theory QoS

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A Neural Network Slab Quality Prediction Analysis Based on a Hybrid Intelligent Optimisation Algorithm

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第3期52卷 673-683页

作者： Li, Yiran Zhang, Chunna School of Applied Technology University of Science and Technology Liaoning Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Liaoning Anshan114051 China

To address the problem of inaccurate prediction of slab quality in continuous casting, an algorithm based on particle swarm optimisation and differential evolution is proposed. The algorithm combines BP neural network prediction method. Firstly, the factors affecting the quality of the slab are analysed and a sufficient number of sample sets are extracted for training;Secondly, the particle swarm optimisation algorithm is optimised, and then the BP neural network is optimised and the chaos mechanism is introduced to increase the continuity of motion of the particles. The population is partitioned hierarchically, and different types of particles are processed separately to improve the global search capability of the algorithm. The differential evolution algorithm is also integrated to optimise cross-selection and increase particle diversity. Finally, a prediction model is built to predict and analyse the sample data. In the experiment, three algorithms are tested for different benchmark functions, namely the comparison of convergence, stability and searchability. The optimisation time comparison is completed, the target curve fit test is performed and the slab quality test results are checked. The experimental results show that the PSO-EIDE algorithm has strong optimisation ability, fast convergence speed and obvious improvement in stability and accuracy. © (2025), (International Association of Engineers). All rights reserved.

关键词： Prediction models

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QFSM: A Novel Quantum Federated Learning Algorithm for Speech Emotion Recognition With Minimal Gated Unit in 5G IoV

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Qu, Zhiguo Chen, Zhixiao Dehdashti, Shahram Tiwari, Prayag Jiangsu Collaborative Innovation Center of Atmospheric Environment the Equipment Technology and the Engineering Research Center of Digital Forensics Ministry of Education and the School of Computer Science Nanjing University of Information Science and Technology Nanjing China School of Computer Science Nanjing University of Information Science and Technology Nanjing China Emmy-Noether Gruppe Theoretisches Quantensystemdesign Lehrstuhl Für Theoretische Informationstechnik Technische Universität München Munich Germany School of Information Technology Halmstad University Halmstad Sweden

The technology of speech emotion recognition (SER) has been widely applied in the field of human-computer interaction within the Internet of Vehicles (IoV). The incorporation of emerging technologies such as artificial intelligence and big data has accelerated the advancement of SER technology. However, this reveals challenges such as limited computational resources, data processing inefficiency, and security and privacy concerns. In recent years, quantum machine learning has been applied to the field of intelligent transportation, which has demonstrated its various advantages, including high prediction accuracy, robust noise resistance, and strong security. This study first integrates quantum federated learning (QFL) into 5G IoV using a quantum minimal gated unit (QMGU) recurrent neural network for local training. Then, it proposes a novel quantum federated learning algorithm, QFSM, to further enhance computational efficiency and privacy protection. Experimental results demonstrate that compared to existing algorithms using quantum long short-term memory network or quantum gated recurrent unit models, the QFSM algorithm has a higher recognition accuracy and faster training convergence rate. It also performs better in terms of privacy protection and noise robustness, enhancing its applicability and practicality. IEEE

关键词： Speech recognition

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Properties and Characteristics of Regolith-Based Materials for Extraterrestrial Construction

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Engineering 2024年第6期37卷 159-181页

作者： Cheng Zhou Yuyue Gao Yan Zhou Wei She Yusheng Shi Lieyun Ding Changwen Miao National Center of Technology Innovation for Digital Construction Huazhong University of Science and TechnologyWuhan 430074China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Southeast UniversityNanjing 214135China State Key Laboratory of Materials Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The construction of extraterrestrial bases has become a new goal in the active exploration of deep *** the construction techniques,in situ resource-based construction is one of the most promising because of its good sustainability and acceptable economic cost,triggering the development of various types of extraterrestrial construction materials.A comprehensive survey and comparison of materials from the perspective of performance was conducted to provide suggestions for material selection and *** types of typical construction materials are discussed in terms of their reliability and applicability in extreme extraterrestrial ***,thermal and optical,and radiation-shielding properties are *** influencing factors and optimization methods for these properties are *** the perspective of material properties,the existing challenges lie in the comprehensive,long-term,and real characterization of regolith-based construction ***,the suggested future directions include the application of high-throughput characterization methods,accelerated durability tests,and conducting extraterrestrial experiments.

关键词： Extraterrestrial construction Characterization Mechanical property Thermal property Optical property Radiation-shielding

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One-step green method to prepare progressive burning gun propellant through gradient denitration strategy

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Defence technology（防务技术） 2023年第4期22卷 135-143页

作者： Shi-ying Li Yu Li Ya-jun Ding Hao Liang Zhong-liang Xiao School of Chemical Engineering Nanjing University of Science and TechnologyNanjing210094China Key Laboratory of Special Energy Materials(Nanjing University of Science and Technology) Ministry of EducationNanjing210094China

Gradiently denitrated gun propellant(GDGP)prepared by a“gradient denitration”strategy is obviously superior in progressive burning performance to the traditional deterred gun ***,the preparation of GDGP employed a tedious two-step method involving organic solvents,which hinders the large-scale preparation of *** this paper,GDGP was successfully prepared via a novelty and environmentally friendly one-step *** obtained samples were characterized by FT-IR,Raman,SEM and *** results showed that the content of nitrate groups gradiently increased from the surface to the core in the surface layer of GDGP and the surface layer of GDGP exhibited a higher compaction than that of raw gun propellant,with a well-preserved nitrocellulose *** denitration process enabled the propellant surface with regressive energy density and good progressive burning performance,as confirmed by oxygen bomb and closed bomb *** the same time,the effects of different solvents on the component loss of propellant were *** result showed that water caused the least component ***,the stability of GDGP was confirmed by methyl-violet *** work not only provided environmentally friendly,simple and economic preparation of GDGP,but also confirmed the stability of GDGP prepared by this method.

关键词： Gradiently denitrated gun propellant One-step green method Denitration Progressive burning Stability

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Efficient Distributed Sparse Relative Similarity Learning

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ACM Transactions on Knowledge Discovery from Data 2025年第3期19卷 1-27页

作者： Yao, Dezhong Li, Sanmu Wang, Zhiwei Zhao, Peilin Wu, Gang Yu, Chen Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Computer Science and Technology Tencent AI Lab Shenzhen China National Super Computing Center in Zhengzhou Zhengzhou University Zhengzhou China

Learning a good similarity measure for large-scale high-dimensional data is a crucial task in machine learning applications, yet it poses a significant challenge. Distributed minibatch Stochastic Gradient Descent (SGD) serves as an efficient optimization method in large-scale distributed training, allowing linear speedup in proportion to the number of workers. However, communication efficiency in distributed SGD requires a sufficiently large minibatch size, presenting two distinct challenges. Firstly, a large minibatch size leads to high memory usage and computational complexity during parallel training of high-dimensional models. Second, a larger batch size of data reduces the convergence rate. To overcome these challenges, we propose an Efficient Distributed Sparse Relative Similarity Learning (EDSRSL) framework. This framework integrates two strategies: local minibatch SGD and sparse relative similarity learning. By effectively reducing the number of updates through synchronous delay while maintaining a large batch size, we address the issue of high computational cost. Additionally, we incorporate sparse model learning into the training process, significantly reducing computational cost. This article also provides theoretical proof that the convergence rate does not decrease significantly with increasing batch size. Various experiments on six high-dimensional real-world datasets demonstrate the efficacy and efficiency of the proposed algorithms, with a communication cost reduction of up to 90.89% and a maximum wall time speedup of 5.66× compared to the baseline methods. © 2025 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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A binary-domain recurrent-like architecture-based dynamic graph neural network

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Autonomous Intelligent Systems 2024年第1期4卷 259-270页

作者： Zi-chao Chen Sui Lin School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

The integration of Dynamic Graph Neural Networks(DGNNs)with Smart Manufacturing is crucial as it enables real-time,adaptive analysis of complex data,leading to enhanced predictive accuracy and operational efficiency in industrial *** address the problem of poor combination effect and low prediction accuracy of current dynamic graph neural networks in spatial and temporal domains,and over-smoothing caused by traditional graph neural networks,a dynamic graph prediction method based on spatiotemporal binary-domain recurrent-like architecture is proposed:Binary Domain Graph Neural Network(BDGNN).The proposed model begins by utilizing a modified Graph Convolutional Network(GCN)without an activation function to extract meaningful graph topology information,ensuring non-redundant *** the temporal domain,Recurrent Neural Network(RNN)and residual systems are employed to facilitate the transfer of dynamic graph node information between learner weights,aiming to mitigate the impact of noise within the graph *** the spatial domain,the AdaBoost(Adaptive Boosting)algorithm is applied to replace the traditional approach of stacking layers in a graph neural *** allows for the utilization of multiple independent graph learners,enabling the extraction of higher-order neighborhood information and alleviating the issue of *** efficacy of BDGNN is evaluated through a series of experiments,with performance metrics including Mean Average Precision(MAP)and Mean Reciprocal Rank(MRR)for link prediction tasks,as well as metrics for traffic speed regression tasks across diverse test *** with other models,the better experiments results demonstrate that BDGNN model can not only better integrate the connection between time and space information,but also extract higher-order neighbor information to alleviate the over-smoothing phenomenon of the original GCN.

关键词： Dynamic graph neural network Smart manufacturing Over-smoothing Link prediction Traffic prediction

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Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

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computers, Materials & Continua 2024年第2期78卷 1977-1993页

作者： Zhiqing Dong Zhao Zhang Hongyan Zhou Xuebo Chen School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China School of Electronic and Information Engineering University of Science and Technology LiaoningAnshan114051China

With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of *** study presents a new approach to the encryption and compression of color *** is predicated on 2D compressed sensing(CS)and the hyperchaotic ***,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong ***,the processed images are con-currently encrypted and compressed using 2D *** them,chaotic sequences replace traditional random measurement matrices to increase the system’s ***,the processed images are re-encrypted using a combination of permutation and diffusion *** addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct *** with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational ***,it has better *** experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.

关键词： Image encryption image compression hyperchaotic system compressed sensing

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