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Friction Stir Spot Welding a Graphene-Reinforced Aluminum Alloy: The Effect of Tool Plunge Depth and Welding Time

Journal of Materials Engineering and Performance 2025年 1-11页

作者： Wu, Tong Liu, Yuding Sui, Xiaochong Li, Zhengwei School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China School of Automotive and Architectural Engineering Harbin Huade University Harbin150025 China School of Architectural Engineering Harbin University of Science and Technology Harbin150080 China School of Material Science and Engineering Harbin Institute of Technology Harbin150001 China

In this work, a graphene-reinforced Al alloy was joined by friction spot welding (FSpW). The effects of welding time and tool plunge depth on the microstructure and mechanical properties of the joints were studied. Results show that FSpW is very suitable to join the graphene-reinforced Al alloy, and sound joints were obtained using wide parameter ranges. Hook bends downwards using small plunge depths of 1 mm and 1.2 mm and short welding times of 2 and 4 s, which then bends upwards at large plunge depth of 1.4 mm and prolonged welding time of 6 s. The sleeve plunge depth has a significant effect on the grain size. The grain size increases from 2.2 to 7 μm when increasing the plunge depth from 1 to 1.4 mm. Mg and C concentrations are obtained at the stir zone, and they react with each other to form Mg2C3. Increasing the plunge depth and the welding time decrease the hardness of the joint. The lap shear failure load of the joint first increases and then becomes stable when increasing the plunge depth, while the joint strength first increases and then decreases when increasing the welding time. © ASM International 2025.

关键词： Aluminum alloys

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Design and Application of Turbine Cascade Partitioned Endwall Profiling

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Journal of Thermal science 2025年第1期34卷 110-128页

作者： ZENG Fei JIANG Ruiqi XUE Xingxu DU Wei LUO Lei ZHOU Xun AECC Hunan Aviation Powerplant Research Institute Zhuzhou 412002China School of Energy Science and Technology Harbin Institute of TechnologyHarbin 150001China Science and Technology on Diesel Engine Turbocharging Laboratory China North Engine Research InstituteTianjin 300270China

The influence of partitioned profiling design based on a large-pitch highly loaded cascade is studied by numerical *** partitioned profile is mainly composed of a pressure-side convex structure near the leading edge and a suction-side convex structure at the midstream and downstream sides of the *** influence of the change in the vertex axial position and peak value of the B-line on the secondary flow control is *** this paper,air(ideal gas)is selected as the flow *** average static pressure at the outlet and the average total temperature at the inlet are kept *** γ-θ is used as the turbulence *** results show that the pressure-side convex structure suppresses the spanwise and pitchwise migration of the inlet flow by adjusting the static pressure distribution of the flow field,so the development of the pressure-side leg of the horseshoe vortex is effectively *** suction-side convex structure adjusts the static pressure distribution of the flow field and increases the included angle between the cross-flow and suction surface,so the accumulation of low-momentum fluid,the development of a corner vortex and the flow separation at the trailing edge of the suction-side surface are all suppressed near the endwall-suction ***,the energy loss coefficient of the large-pitch highly loaded cascade is decreased from 0.0564 to 0.0485,representing a 25% reduction in secondary flow losses.

关键词： large-pitch highly loaded cascade highly loaded design non-axisymmetrical endwall design secondary flow control partitioned endwall profiling

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RoPe-Door: Toward Robust and Persistent Backdoor Data Poisoning Attacks in Federated Learning

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IEEE Network 2025年第3期39卷 302-310页

作者： Liu, Ye Chang, Shan Li, Denghui Shi, Shaohuai Li, Bo Jiangxi Normal University School of Computer and Information Engineering Nanchang330022 China Donghua University School of Computer Science and Technology Shanghai201620 China Harbin Institute of Technology School of Computer Science and Technology Shenzhen518057 China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Sai Kung Hong Kong

Federated Learning (FL) enables privacy-preserving collaborative training and builds a federation through exchanges of immutable data such as model parameters or gradient updates. FL remains vulnerable to a variety of attacks during critical processes like local model training and parameter transmission, in which the backdoor attack is particularly evident. In this paper, we propose a novel backdoor data poisoning attack method, RoPe-Door, using a trigger generation algorithm to improve the robustness and persistence of attacks even under Byzantine aggregation methods. We conduct extensive experiments on four image classification tasks to evaluate the effectiveness of RoPe-Door. The experimental results demonstrate that, compared to backdoor attacks using random triggers, RoPe-Door exhibits significant advantages in robustness, persistence, and attack effectiveness under both IID and Non-IID data settings. © 1986-2012 IEEE.

关键词： Federated learning

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Optoelectronic-Coupled-Driven Microrobot for Biological Cargo Transport in Conductive Isosmotic Glucose Solution

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ACS Applied Materials and Interfaces 2025年第19期17卷 28425-28435页

作者： Zhuang, Rencheng Chang, Xiaocong Sha, Jinrui Yu, Zehao Shi, Enbo Lu, Minqiao Liu, Junmin Zhang, Guangyu Zhou, Dekai Li, Longqiu State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Chongqing Research Institute Harbin Institute of Technology Chongqing400722 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450000 China School of Life Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China

Electric field-driven micro/nanorobots, as micro/nanodevices with autonomous motion capability, have emerged as promising candidates for targeted cargo delivery in biomedical applications due to their advantages of label-free operation, selectivity, and controllability. In biological systems, many biological cargos need to be operated in conductive isosmotic solutions to ensure their viability. However, in the conductive solution, electric field-driven micro/nanorobots exhibit significantly reduced propulsion performance, despite retaining the capability to manipulate cargos by the dielectrophoretic force. This limitation restricts the wider applicability of electric field-driven micro/nanorobots in biomedical fields. This paper presents a novel optoelectronic-coupled-driven α-Fe2O3@aTiO2/Au microrobot, which exhibits significantly improved mobility and enables biological cargo transportation in the conductive isosmotic glucose solution. Benefiting from the flowerlike surface structure and composite photocatalytic material, the proposed microrobot exhibits enhanced photocatalytic capability, enabling efficient propulsion in glucose solution under light irradiation. In addition, the motion behavior of the microrobot under light, electric, and optoelectronic-coupled fields is investigated. It is found that the speed of the microrobot could exceed 300 μm/s under coupled fields, which is more than ten times faster than that of previously reported electric field-driven micro/nanorobots. Due to the magnetic property, the proposed microrobot can be precisely navigated under the guidance of an external uniform magnetic field. Furthermore, the proposed microrobot can achieve the transportation of various biological cargos in a conductive isosmotic glucose solution. The proposed microrobot opens a new avenue for targeted delivery and holds great potential for applications in the biological and pharmaceutical fields. © 2025 American Chemical Society.

关键词： Medical nanotechnology

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Using DTL-MD with GANs and ResNet for Malicious Code Detection

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第14期49卷 63-78页

作者： Li, Yiming Xie, Tao Mei, Dongdong Department of Computer Science and Technology School of Computer Science and Engineering Ningxia Institute of Science and Technology Shizuishan753000 China

This study proposes a malicious code detection model DTL-MD based on deep transfer learning, which aims to improve the detection accuracy of existing methods in complex malicious code and data scarcity. In the feature extraction process, the weighted sum method of GIST and LBP features is used to combine the advantages of the two features. Online transfer learning is used to reduce the data distribution difference between the target domain and the source domain. The model uses ResNet50V2 as the backbone network and combines SimAM to enhance the feature extraction and representation capabilities. In addition, in order to further improve the robustness of detection, GAN is used to generate malicious code variants and expand the training data set. In the experiment, the public CICIDS 2017 data set is used for model training and testing. The performance test results show that when the threshold is 0.7, the accuracy of DTL-MD is 95.8% and the F1 score is 0.93. In a performance test involving 30,000 samples, the throughput of the DTL-MD model under Trojans, viruses, worms, and adware is 11, 12, 11, and 12 tasks/s, respectively, and the inference time is 211, 225, 239, and 234 samples/s, respectively. Compared with GAN, DTL-MD increases the throughput by about 10% and the inference speed by about 15%. The research aims to provide new ideas for improving the intelligence and automation level of malicious code detection technology, which has certain application value and practical significance. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Feature Selection

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Exponential Stability of Fractional-Order Fuzzy Multilayer Networks With Short Memory and Noninstantaneous Impulses via Intermittent Control

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IEEE Transactions on Fuzzy Systems 2025年第5期33卷 1639-1649页

作者： Xu, Yao Chen, Zui Li, Wenxue Wu, Yongbao Nanjing University of Posts and Telecommunications School of Computer Science Nanjing210023 China Harbin Institute of Technology Weihai Department of Computer Science and Technology Weihai264209 China Harbin Institute of Technology Weihai Department of Mathematics Weihai264209 China Southeast University School of Automation Nanjing210096 China

Many practical processes in the actual world may suffer from nonnegligible instantaneous state resets and then persist for a set amount of time, which can be characterized by noninstantaneous impulses. In this article, intermittently controlled fractional-order fuzzy multilayer complex networks with short memory and noninstantaneous impulses are considered, which give rise to a new, hybrid dynamical system that offers a wide range of applications. By employing a discontinuously intermittent control scheme, the exponential stability issue of the above-mentioned networks is studied and supported by the Lyapunov method and graph theory. In the analysis of exponential stability, stabilized and destabilized noninstantaneous impulsive effects are discussed respectively. Ultimately, main results are applied in the typical model of fractional-order competitive neural networks, and illustrative numerical simulations are conducted to show the effectiveness of theoretical analysis. © 1993-2012 IEEE.

关键词： Lyapunov methods

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Nonspherical photonic scatterers and design criterion for efficient passive daytime radiative cooling

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science China(Technological sciences) 2025年第2期68卷 1-14页

作者： Xinping ZHANG Tairong KANG Fuqiang WANG Xiang LI Hongliang YI School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China College of New Energy Harbin Institute of Technology at WeihaiWeihai 264209China Construction Eco-Environmental Protection Technology Co. Ltd.Suzhou 215123China

Passive daytime radiative cooling(PDRC)exhibits efficient cooling performance to reduce global fossil energy consumption and has attracted enormous *** efficient PDRC technology for achieving daytime subambient cooling is supposed to exhibit ultra-high solar reflectivity and infrared emissivity within atmospheric windows,among which ultra-high solar reflectivity is the principal *** most PDRC technologies,spherical particles are selected as scatterers to achieve high solar reflectivity because the Mie scattering effect of spherical scatterers can provide a high scattering ***,the weak backward scattering of spherical scatterers remains a *** this study,several nonspherical scatterers with strong backward scattering are introduced and researched *** numerical analysis results indicate that pyramidal scatterers provide the strongest backward scattering and square/circular scatterers exhibit the highest scattering ***,by considering scattering efficiency and asymmetry factor comprehensively,a dimensionless evaluation parameter is proposed,which can be employed as a quantitative design criterion to achieve the optimal-object-oriented designing of superior *** work can provide an innovative strategy for designing efficient passive daytime radiative cooling materials.

关键词： radiative cooling nonspherical scatterers solar reflectivity backward scattering design criterion

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Limb movement detection and analysis based on visual recognition of human posture

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Discover Artificial Intelligence 2025年第1期5卷 1-12页

作者： Xiao, Zhiguo Wang, Chunxiang Ding, Tianjiao Shen, Xiangfeng Li, Xinyuan Li, Dongni School of Computer Science & Technology Beijing Institute of Technology Beijing100811 China School of Computer Science Technology Changchun University Changchun130022 China

Current motion detection and evaluation technologies face challenges such as limited scalability, imprecise feedback, and lack of personalized guidance. To address these challenges, this research integrated efficient BlazePose technology with pioneering DW_KNN* algorithm, resulting in the remarkable accuracy of 98.2% in action recognition and showcasing outstanding scalability. Furthermore, the established ACLstm time series prediction model could comprehensively analyze historical sports data and associated factors of users. In Rehab dataset, MAE(Mean Absolute Error, MAE) loss was 1.383 for motion count and 0.508 for motion time. This innovative framework delivered precise feedback and tailored guidance for physical exercise and medical rehabilitation. © The Author(s) 2025.

关键词： Time series

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Existence and uniqueness of mean field equilibrium in continuous bandit game

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science China(Information sciences) 2025年第3期68卷 395-396页

作者： Xiong WANG Yuqing LI Riheng JIA School of Computer Science and Technology Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan University Wuhan University Shenzhen Research Institute School of Computer Science and Technology Zhejiang Normal University

Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent systems with bandit feedback is to explore and understand the equilibrium state to ensure stable and tractable system performance.

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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance with EDA and Multi-Channel CNN

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IEEE Access 2025年 13卷 31978-31991页

作者： Wahyu Trisna, Komang Huang, Jinjie Chen, Yuanjian Gede Juliana Eka Putra, I. Harbin University of Science and Technology School of Computer Science and Technology Harbin150080 China Primakara University Department of Informatic Engineering Denpasar Bali80226 Indonesia Harbin University of Science and Technology Key Laboratory of Advanced Manufacturing and Intelligence Technology Harbin150080 China

The rapid growth of social media has revolutionized the way individuals share and access opinions, generating vast amounts of textual data containing diverse sentiments. Sentiment analysis enables organizations to derive valuable insights from this data, facilitating improved decision-making. However, the limited availability of labeled datasets and challenges related to data imbalance often hinder the development of robust sentiment analysis models. In this study, we propose a novel framework dynamic Easy Data Augmentation (EDA) technique with a Multi-Channel Convolutional Neural Network (MCNN) to address these issues. The EDA techniques including synonym replacement (SR), random insertion (RI), random deletion (RD), and random swap (RS), enrich the training data by introducing diversity, thereby enhancing model robustness. The MCNN architecture effectively captures local patterns in text using multiple filter sizes, enabling comprehensive feature extraction with low computational overhead. Furthermore, the integration of Word2Vec embeddings ensures meaningful text representation, leveraging context-independent word relationships for improved sentiment analysis. Experimental evaluations demonstrate the effectiveness of the proposed approach, highlighting significant improvements in F1-score compared to baseline models. The findings underscore the potential of dynamic text augmentation and efficient deep learning architectures to overcome the challenges of limited training data, offering a scalable solution for sentiment analysis in real-world applications. Additionally, the proposed model achieves an average performance improvement of 11.34% over previous models. © 2025 The Authors.

关键词： Convolutional neural networks

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