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Nanotwining induced by tensile fatigue and dynamic impact of laser powder bed fusion additively manufactured CoCrFeNi high-entropy alloy

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Journal of Materials Science & technology 2024年第16期183卷 241-257页

作者： Guoqing Huang Bo Li Yinan Chen Fuzhen Xuan School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Additive Manufacturing and Intelligent Equipment Research Institute East China University of Science and TechnologyShanghai 200237China Shanghai Collaborative Innovation Center for High-end Equipment Reliability Shanghai 200237China

The laser powder bed fusion(L-PBF)additively manufactured CoCrFeNi high-entropy alloy(HEA),with face-centered cubic(FCC)crystal structure,demonstrates better comprehensive mechanical properties in the building direction(BD).Loading quasi-static,dynamic fatigue,and dynamic separated Hopkinson press bar(SHPB)impact stress conditions along the BD of the L-PBF processed HEA exhibit intriguing mi-crostructural evolution *** L-PBF generates hierarchical dislocation grids containing nu-merous cell substructures within the HEA FCC grains,impeding dislocation motion during deformation and improving the *** subjected to dynamic fatigue loading,the dislocation grids restrict the mean free path of dislocations and thus trigger the activation of abundant stacking ***,nu-merous nanotwins form near the end of the fatigue *** twinning systems can also be activated under dynamic high-speed impact *** at a low temperature of 77 K,the stacking fault energy of the CoCrFeNi HEA decreases,resulting in increased activation of nanotwins,exhibiting excep-tional toughness and resistance to dynamic *** twin boundaries also impede dislocation movement for the strain *** findings hold valuable implications for the study of additively manufactured HEA parts working in extreme environments.

关键词： High-entropy alloy Nanotwins Fatigue Impact behavior Additive manufacturing

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Active Magnetic Compensation Based on Parametric Resonance Magnetometer

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Journal of shanghai Jiaotong university(Science) 2024年第2期29卷 280-289页

作者：郭阳李绍良黄艺明骆曼箬刘华 School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Spacefight Control Technology Shanghai Key Laboratory of Space Intelligent Control TechnologyShanghai Engineer Research Center of InertiaShanghai 201109China

Based on the parametric resonance magnetometer(PRM)theory,this paper establishes an experimen-tal system of *** experimental results are consistent with the theoretical predictions.A PRM has been developed with sensitivity of 0.5 pT/Hz^(1/2),which can detect the magnitude of residual magnetic field;furthermore,a proportion-integration-differentiation(PID)closed-loop magnetic compensation system of the residual magnetic field also has been *** with open-loop compensation,the PID closed-loop compensation reduces the average value of the residual magnetic field in the z-axis direction from 0.0244nT to-0.0023nT,and the mean-square error from 0.2083 nT to 0.0691 *** the same way,the average value of the residual magnetic field in the y-axis direction is reduced from 0.0816nT to-0.0042nT,and the mean-square error from 0.1316nT to 0.0461 *** magnitude of residual magnetic fields in both directions is decreased to the order of picotesla(pT).In addition,based on the signal waveforms of the magnetometer,a method of verifying the effect of magnetic compensation is proposed.

关键词： magnetometer parametric resonance nuclear magnetic resonance gyroscope magnetic compensa-tion proportion-integration-differentiation(PID)

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Prospective Role of Foundation Models in Advancing Autonomous Vehicles

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research 2025年第1期7卷 667-691页

作者： Jianhua Wu Bingzhao Gao Jincheng Gao Jianhao Yu Hongqing Chu Qiankun Yu Xun Gong Yi Chang H Eric Tseng Hong Chen Jie Chen School of Automotive Studies Tongji UniversityShanghai 201804China Frontiers Science Center for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China SAIC Intelligent Technology Shanghai 201805China College of Artificial Intelligence Jilin UniversityChangchun 130012China Research and Advanced Engineering Ford Motor CompanyDearbornMI 48124USA College of Electronic and Information Engineering Tongji UniversityShanghai 201804China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai 201210China

With the development of artificial intelligence and breakthroughs in deep learning,large-scale foundation models(FMs),such as generative pre-trained transformer(GPT),Sora,etc.,have achieved remarkable results in many fields including natural language processing and computer *** application of FMs in autonomous driving holds considerable *** example,they can contribute to enhancing scene understanding and *** pre-training on rich linguistic and visual data,FMs can understand and interpret various elements in a driving scene,and provide cognitive reasoning to give linguistic and action instructions for driving decisions and ***,FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data *** enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving *** testament to the potential of FMs'applications lies in world models,exemplified by the DREAMER series,which showcases the ability to comprehend physical laws and *** from massive data under the paradigm of self-supervised learning,world models can generate unseen yet plausible driving environments,facilitating the enhancement in the prediction of road users'behaviors and the off-line training of driving *** this paper,we synthesize the applications and future trends of FMs in autonomous *** utilizing the powerful capabilities of FMs,we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving,consequently advancing overall safety in this domain.

关键词： autonomous driving computer visionthe artificial intelligence natural language processing deep learninglarge scale autonomous vehicles understand interpr enhancing scene understanding reasoningby

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SEED-VII: A Multimodal Dataset of Six Basic Emotions with Continuous Labels for Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第2期16卷 969-985页

作者： Jiang, Wei-Bang Liu, Xuan-Hao Zheng, Wei-Long Lu, Bao-Liang Shanghai Jiao Tong University Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Shanghai200240 China

Recognizing emotions from physiological signals is a topic that has garnered widespread interest, and research continues to develop novel techniques for perceiving emotions. However, the emergence of deep learning has highlighted the need for comprehensive and high-quality emotional datasets that enable the accurate decoding of human emotions. To systematically explore human emotions, we develop a multimodal dataset consisting of six basic (happiness, sadness, fear, disgust, surprise, and anger) emotions and the neutral emotion, named SEED-VII. This multimodal dataset includes electroencephalography (EEG) and eye movement signals. The seven emotions in SEED-VII are elicited by 80 different videos and fully investigated with continuous labels that indicate the intensity levels of the corresponding emotions. Additionally, we propose a novel Multimodal Adaptive Emotion Transformer (MAET), that can flexibly process both unimodal and multimodal inputs. Adversarial training is utilized in the MAET to mitigate subject discrepancies, which enhances domain generalization. Our extensive experiments, encompassing both subject-dependent and cross-subject conditions, demonstrate the superior performance of the MAET in terms of handling various inputs. Continuous labels are used to filter the data with high emotional intensity, and this strategy is proven to be effective for attaining improved emotion recognition performance. Furthermore, complementary properties between the EEG signals and eye movements and stable neural patterns of the seven emotions are observed. © 2010-2012 IEEE.

关键词： Eye movements

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From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics

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IEEE Transactions on Visualization and Computer Graphics 2025年第05期31卷 3481-3491页

作者： Wu, Yuchen Gao, Shenghan Zhang, Shizhen Dou, Xiaofeng Wang, Xingbo Li, Quan ShanghaiTech University School of Information Science and Technology Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai201210 China Cornell University Weill Cornell Medical College United States

Visual Analytics (VA) researchers frequently collaborate closely with domain experts to derive requirements and select appropriate solutions to fulfill these requirements. Despite strides made in exploring requirement and solution spaces, challenges persist due to the absence of guidance in the initial consideration space and the lack of shared problem-solving knowledge, often resulting in suboptimal solutions. To address these issues, we conducted an empirical study of VA research, with a focus on mapping the relations between requirement and solution spaces. Analyzing 220 VA papers, we formulate refined topologies for data, requirements, and solutions. We propose conceptualizing the connections between requirements, data, and solutions through knowledge graphs and utilizing solution paths to encapsulate fundamental problem-solving knowledge in visual analytics research. Through the integration of solution paths into a graph and analyzing their interconnections, we identified a subset of problem-driven design patterns that demonstrated the efficacy of our approach. By externalizing problem-solving knowledge and formulating problem-driven design patterns, our aim is to streamline the exploration of consideration space, facilitating the inclusion of "good"solutions, and establish a benchmark for shared design decisions among researchers and readers. © 1995-2012 IEEE.

关键词： Visual analytics

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Detection and Characterization of Defects in Additive Manufacturing by Polarization-Based Imaging System

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Chinese Journal of Mechanical engineering 2023年第5期36卷 120-140页

作者： Xing Peng Lingbao Kong Shanghai Engineering Research Center of Ultra-precision Optical Manufacturing School of Information Science and TechnologyFudan UniversityShanghai 200438China College of Intelligent Science and Technology National University of Defense TechnologyChangsha 410003HunanChina

Additive manufacturing (AM) technology such as selective laser melting (SLM) often produces a high refection phenomenon that makes defect detection and information extraction challenging. Meanwhile, it is essential to establish a characterization method for defect analysis to provide sufcient information for process diagnosis and optimization. However, there is still a lack of universal standards for the characterization of defects in SLM parts. In this study, a polarization-based imaging system was proposed, and a set of characterization parameters for SLM defects was established. The contrast, defect contour information, and high refection suppression efect of the SLM part defects were analyzed. Comparative analysis was conducted on defect characterization parameters, including geometric and texture parameters. The experimental results demonstrated the efects of the polarization imaging system and verifed the feasibility of the defect feature extraction and characterization method. The research work provides an efective solution for defect detection and helps to establish a universal standard for defect characterization in additive manufacturing.

关键词： Additive manufacturing Selective laser melting High refection Defect characterization Polarizationbased imaging

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Multi-Scale Feature Fusion and Advanced Representation Learning for Multi Label Image Classification

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Computers, Materials & Continua 2025年第3期82卷 5285-5306页

作者： Naikang Zhong Xiao Lin Wen Du Jin Shi Institute of Artificial Intelligence on Education Research College of InformationMechanical and Electrical EngineeringShanghai Normal UniversityShanghai200234China Lab for Educational Big Data and Policymaking Ministry of EducationShanghai Normal UniversityShanghai200234China Shanghai Intelligent Education Big Data Engineering Technology Research Center Shanghai Normal UniversityShanghai200234China Shanghai Online Education Research Base for Primary and Secondary Schools Shanghai200234China DS Information Technology Co. Ltd.Shanghai200032China Faculty of Innovation Engineering Macao university of Science and TechnologyMacao999078China

Multi-label image classification is a challenging task due to the diverse sizes and complex backgrounds of objects in *** class-specific precise representations at different scales is a key aspect of feature ***,existing methods often rely on the single-scale deep feature,neglecting shallow and deeper layer features,which poses challenges when predicting objects of varying scales within the same *** some studies have explored multi-scale features,they rarely address the flow of information between scales or efficiently obtain class-specific precise representations for features at different *** address these issues,we propose a two-stage,three-branch Transformer-based *** first stage incorporates multi-scale image feature extraction and hierarchical scale *** design enables the model to consider objects at various scales while enhancing the flow of information across different feature scales,improving the model’s generalization to diverse object *** second stage includes a global feature enhancement module and a region selection *** global feature enhancement module strengthens interconnections between different image regions,mitigating the issue of incomplete represen-tations,while the region selection module models the cross-modal relationships between image features and ***,these components enable the efficient acquisition of class-specific precise feature *** experiments on public datasets,including COCO2014,VOC2007,and VOC2012,demonstrate the effectiveness of our proposed *** approach achieves consistent performance gains of 0.3%,0.4%,and 0.2%over state-of-the-art methods on the three datasets,*** results validate the reliability and superiority of our approach for multi-label image classification.

关键词： Image classification multi-label multi scale attention mechanisms feature fusion

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Degradable nanocatalyst enables antitumor/antibacterial therapy and promotion of wound healing for diabetes via self-enhanced cascading reaction

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Chinese Chemical Letters 2023年第7期34卷 155-161页

作者： Xiang Wang Cheng Ding Ziwen Zhang Chunlin Li Dongmiao Cao Linjing Zhao Guoying Deng Yu Luo Chunping Yuan Jie Lu Xijian Liu School of Chemistry and Chemical Engineering Shanghai Engineering Technology Research Center for Pharmaceutical Intelligent EquipmentShanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNAInstitute for Frontier Medical TechnologyShanghai University of Engineering ScienceShanghai201620China Affiliated Sixth People's Hospital Shanghai JiaoTong UniversityShanghai 200233China Trauma Center Shanghai General HospitalShanghai Jiaotong University School of MedicineShanghai 201620China

Diabetic patients often have problems such as residual tumor and wound infection after tumor resection,causing severe clinical *** is urgent to develop effective therapies to reach oncotherapy/antiinfection/promotion of wound healing combined ***,we propose CS/MnO_(2)-GO_x (CMGO_x)nanocatalysts for the specific catalytic generation of ~·OH to inhibit tumors and bacteria in a hyperglycemic *** good biocompatible chitosan (CS),as a carrier for the catalyst,exhibits excellent antibacterial effect as well as promotes wound *** oxidase (GO_x) is loaded on the surface of CS nanoparticles to generate H_(2)O_(2) and gluconic acid by consuming glucose (starvation therapy,ST) and O_(2).The MnO_(2) depletes glutathione (GSH) to produce Mn^(2+),amplifying oxidative stress and further promoting the activity of Mn^(2+)-mediated Fenton-like reaction to produce~·OH (chemodynamic therapy,CDT)in weak acidic ***,the produced gluconic acid lowers the p H of the environment,enhancing chemodynamic therapy (ECDT).The tumor cells and bacteria are efficiently eliminated by the synergistic effect of ST and *** MnO_(2) nanoparticles at neutral environment decomposes H_(2)O_(2) into O_(2),which cooperate with CS to promote *** self-enhanced cascade reaction of CMGO_x in situ exhibits excellent effects of antitumor/antibacterial therapy and promotion of wound healing,offering a promising integrated treatment for diabetic patients after tumor surgical resection.

关键词： Self-cascade reaction Starvation therapy Chemodynamic therapy Antitumor Antibacterial Wound healing

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Background Subtraction-based Unlearned Hazardous Object Detection Algorithm for Ceiling Environments

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Journal of Institute of Control, robotics and Systems 2025年第4期31卷 334-342页

作者： Jeon, Jae Woo Kim, Sung Jae Suh, Jin Ho Department of Intelligent Robot Engineering Pukyong National University Korea Republic of The Industrial Science Technology Research Center Pukyong National University Korea Republic of Major of Mechanical System Engineering Pukyong National University Korea Republic of

We propose a background subtraction-based algorithm that uses images from an RGB-D camera to detect unlearned hazardous objects in ceiling environments, thereby facilitating efficient ceiling exploration. We constructed a dataset by compiling various images of ceiling structures and employed the YOLOv8s-seg model to recognize ceiling components. Recognized ceiling structures and regions exceeding a specified depth threshold were designated as background and removed in the first stage. A U-map based on depth information was then used to detect object regions, which enabled the identification of various types of potentially hazardous objects. The positions of the detected objects were continuously updated using a Kalman filter based tracking model, and their relative positions were visually displayed on a 2D map. To validate the performance of the algorithm, we implemented it in a system and conducted hazardous object detection experiments in a ceiling-simulated testbed and an actual ceiling environment. The findings confirmed the applicability of the algorithm in real-world settings. © ICROS 2025.

关键词： Kalman filters

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Active learning attraction basins of dynamical system

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Chinese Physics B 2025年第5期34卷 115-122页

作者： Xiao-Wei Cao Xiao-Lei Ru Gang Yan MOE Key Laboratory of Advanced Micro-Structured Materials and School of Physical Science and EngineeringTongji UniversityShanghai 200092China National Key Laboratory of Autonomous Intelligent Unmanned Systems MOE Frontiers Science Center for Intelligent Autonomous Systemsand Shanghai Research Institute of Intelligence Science and TechnologyTongji UniversityShanghai 200092China

Dynamical systems often exhibit multiple attractors representing significantly different functioning conditions.A global map of attraction basins can offer valuable guidance for stabilizing or transitioning system *** a map can be constructed without prior system knowledge by identifying attractors across a sufficient number of points in the state ***,determining the attractor for each initial state can be a laborious ***,we tackle the challenge of reconstructing attraction basins using as few initial points as *** each iteration of our approach,informative points are selected through random seeding and are driven along the current classification boundary,promoting the eventual selection of points that are both diverse and *** results across various experimental dynamical systems demonstrate that our approach requires fewer points than baseline methods while achieving comparable mapping ***,the reconstructed map allows us to accurately estimate the minimum escape distance required to transition the system state to a target basin.

关键词： complex system attraction basin active learning

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