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Solid state recycling of used aluminum alloy beverage cans by thermomechanical consolidation

Heat Treatment and Surface engineering 2022年第1期4卷 90-98页

作者： Wang, Ziyi Yu, Yuanping Jin, Yu Li, Zhuolun Sun, Song Xu, Haoran Wu, Chengxun Zhang, Deliang School of Material Science and Engineering Northeastern University Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Shenyang China

Solid-state recycling of used aluminum alloy beverage cans was accomplished by thermomechanical consolidation of the sheet fragments produced by shredding the cans. Different samples were obtained using two thermomechanical consolidation routes, one involving direct hot extrusion of a sheet fragment compact and the other involving upset hot-forging of a sheet fragment compact followed by hot extrusion of the forged ingot. The microstructures and mechanical properties of the samples were investigated. It was found that the samples contained less pores and exhibited better mechanical properties with a higher extrusion temperature and involving upset forging than with only hot extrusion, the highest tensile strength is 209.5 MPa and the largest elongation to fracture is 29.1%. The surface layers of the samples exhibited a clearly higher strength and tensile ductility than the interior. They also showed significantly different fracture behaviors, with the former being like fully ductile fracture and the latter involving delamination of the sheet fragments, suggesting that the bonding between the fragments is significantly stronger in the surface layer, possibly due to a higher amount of plastic deformation in it. Overall, the best quality solid state recycled material has tensile properties comparable with those of wrought aluminum alloy with the same composition. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： mechanical properties microstructure solid state recycling thermomechanical consolidation of sheet fragments Used aluminum beverage cans

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Multicriteria Fatigue Detection with Rapid Facial Tracking and Individualized Thresholds

Multicriteria Fatigue Detection with Rapid Facial Tracking a...

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2023 International Conference on Sensing, Measurement and data Analytics in the Era of Artificial Intelligence, ICSMD 2023

作者： Wang, Yixuan Li, Qing Wu, Yutian Ma, Jinge School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing China School of Mathematics and Physics University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798350318012

Fatigue driving is one of the main causes of traffic accidents. Detecting fatigue driving can identify the possible fatigue state of the driver and issue warnings to prevent potential dangerous situations. At present, there exist challenges for available detection methods, which contains lack of real-time, low accuracy and robustness. As is a solution to problems above, the method proposed in this paper improves comprehensive performance by raising 3 new algorithms: (1) rapid face tracking algorithm, which can locate and track the driver's facial region in real time under complex lighting and background conditions, improving the detection efficiency and accuracy;(2) multi-criteria fusion algorithm, which can comprehensively consider various physiological and behavioral features, as well as their interrelationships, and output a comprehensive fatigue score, improving the detection sensitivity and robustness;(3) individualized threshold algorithm, which can dynamically adjust the fatigue threshold according to the individual differences and habits of each driver, improving the detection adaptability and personalization. The experiment results with different subjects under various fatigue driving behaviors demonstrate that the proposed approach is more accurate, fast and robust than existing ones in terms of driver identification recognition and fatigue detection. © 2023 IEEE.

关键词： Face recognition

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Adaptive Spatial-Temporal Aware Graph Learning for EEG-Based Emotion Recognition

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Cyborg and Bionic Systems 2024年第1期5卷 461-471页

作者： Weishan Ye Jiyuan Wang Lin Chen Lifei Dai Zhe Sun Zhen Liang School of Biomedical Engineering Medical SchoolShenzhen UniversityShenzhenChina Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging ShenzhenChina School of Clinical Medicine Harbin Medical UniversityHarbinChina Faculty of Health Data Science and Faculty of Medicine Juntendo UniversityTokyoJapan International Health Science Innovation Center Medical SchoolShenzhen UniversityShenzhenChina

An intelligent emotion recognition system based on electroencephalography(EEG)signals shows considerable potential in various domains such as healthcare,entertainment,and education,thanks to its portability,high temporal resolution,and real-time ***,the existing research in this field faces limitations stemming from the nonstationary nature and individual variability of EEG *** this study,we present a novel EEG emotion recognition model,named GraphEmotionNet,designed to enhance the accuracy of EEG-based emotion recognition through the incorporation of a spatiotemporal attention mechanism and transfer *** proposed GraphEmotionNet model can effectively learn the intrinsic connections between EEG channels and construct an adaptive *** graph’s adaptive nature is crucial in optimizing spatial-temporal graph convolutions,which in turn enhances spatial-temporal feature characterization and contributes to the process of emotion ***,an integration of domain adaptation aligns the extracted features across different domains,further alleviating the impact of individual EEG *** evaluate the model performance on two benchmark databases,employing two types of cross-validation protocols:within-subject cross-validation and cross-subject *** experimental results affirm the model’s efficacy in extracting EEG features linked to emotional semantics and demonstrate its promising performance in emotion recognition.

关键词： enhance acc Emotion Recognition EEG eeg emotion recognition modelnamed Graph Learning Domain Adaptation Transfer Learning Spatiotemporal Attention

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Control Method for Connecting the Elevated Expressway with the Ground Intersection Based on Reflective Film Material Guidance 10

Control Method for Connecting the Elevated Expressway with t...

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10th Annual International Conference on Material Science and Environmental engineering, MSEE 2022

作者： Li, Yuqi Zhan, Xuejuan Liang, Zijun Wang, Ruihan Xiao, Yun Peng, Min School of Urban Construction and Transportation Hefei University China Anhui Province Transportation Big Data Analysis and Application Engineering Laboratory China Key Laboratory of Traffic Information and Safety of Anhui Higher Education Institutes Anhui Sanlian University China

With the rapid development of elevated expressways, urban elevated expressways bear more and more traffic volume, and the adoption of environmental protection materials has become an inevitable trend in the development of elevated expressways. a control method for connecting the elevated expressway with the ground intersection based on reflective film material is presented. Firstly, the green reflective film material is used to guide the connecting section of the elevated expressway and the ground intersection. Then, the corresponding signal timing method is proposed to optimize the traffic flow time between the elevated expressway and the ground ***, through the analysis of the VISSIM traffic simulation software to evaluate the results show that the method is based on the reflective film material can effectively guide the elevated expressway with the ground intersection connection section, under the premise by signal optimization technology to further improve the traffic efficiency, effectively reduces the overhead elevated expressway with the ground intersection connection number of the conflicts, It provides a basis for the research on the connection section between the elevated expressway and the ground intersection based on reflective film material guidance. © Published under licence by IOP Publishing Ltd.

关键词： Computer software

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Dynamic Locomotion of Quadruped Robot in Sloping Terrain 6

Dynamic Locomotion of Quadruped Robot in Sloping Terrain

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Chen, Donglin Cong, Dehong Song, Xiangman Northeastern University National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang110819 China Northeastern University Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China

ISBN: (纸本)9798350316155

In order to improve the locomotion capability of quadruped robot in the sloping terrain and enhance whose adaptability to the environment, this paper proposes a method to realize dynamic locomotion of quadruped robot in sloping terrain completely based on model predictive control (MPC) and proprioception. According to the foot contact signal and the robot body posture information measured by inertial measurement unit (IMU), quadruped robot actively changes whose body posture to adapt to different sloping terrains. This paper builds quadruped robot virtual prototype and test terrain in Webots simulation environment. The experimental results show that with this method, the roll angle fluctuation range of the quadruped robot is less than 0.05rad and the yaw angle fluctuation range is not more than 0.003rad. At the same time, when the angle of slope changes, the terrain adaptation time of the quadruped robot is less than 1.8s. The above results show that quadruped robot has excellent movement ability in sloping terrain and environmental adaptability under the condition of ensuring stability with the method proposed in this paper. © 2023 IEEE.

关键词： Model predictive control

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TSKE: A Dual-Branch Model for knowledge Graph Embedding with Joint Textual and Structural Information 11th

TSKE: A Dual-Branch Model for Knowledge Graph Embedding wit...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Deng, Weibin Xiong, Yuanyuan Jiang, Ziqun Yu, Hong Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing China Smart Posts Engineering Technology Research Center Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education Chongqing China

ISBN: (纸本)9783031927430

knowledge graphs (KGs) serve as critical structured representations of the real world, modeling entities and their complex relational patterns. While traditional knowledge graph embedding (KGE) methods excel at capturing structural regularities through geometric or tensor operations, they have limitations in effectively integrating structural and textual information. To address this limitation, we propose TSKE, a novel dual-branch architecture that effectively integrates both textual and structural information. The text branch employs language models to encode textual descriptions, generating context-aware semantic representations. Simultaneously, the structure branch introduces a multi-scale dilated attention mechanism that captures local neighborhood patterns and global graph dependencies through hierarchical receptive fields. The efficient channel attention further enhances feature selectivity by adaptively filtering noise and emphasizing feature relevance. TSKE incorporates an adaptive fusion module that dynamically adjusts the contribution weights of textual and structural features. Experimental results demonstrate TSKE’s superior performance in KGE. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： knowledge graph

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Service Decision Mechanism Based On Traffic Flow Prediction in the Internet of Vehicles 23

Service Decision Mechanism Based On Traffic Flow Prediction ...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Hu, Yanzhe Feng, Chenyuan Jiang, Wei Shi, Wenzhe Feng, Daquan Shenzhen University Shenzhen Key Laboratory of Digital Creative Technology Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication Shenzhen China College of Information Engineering Zhejiang University of Technology Zhejiang Hangzhou China Zte Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology China

ISBN: (纸本)9798350325959

The service time of Road-Side Units (RSUs) for vehicle users will directly affect the Quality of Service (QoS) in the Internet of Vehicles (IoV), and it is related to the traffic flow and service decisions. Consequently, a sophisticated service decision mechanism based on the traffic flow prediction is necessary beforehand in order to optimize QoS. In this work, we propose a service decision based on traffic flow prediction to reduce the service waiting time of vehicles. Firstly, we propose a traffic flow prediction model based on deep learning. Convolutional Neural Network (CNN) is used to capture spatial data in order to handle the complicated road network layout in metropolitan roads. First, to reveal people's travel patterns, temporal features are captured by two different models. While short-term features are captured from historical data by Auto-Encoder, daily period feature as well as weekly period feature are captured from bi-directional data by Bidirectional Long Short-Term Memory (Bi-LSTM). Second, by simulating the process of RSUs serving vehicles using a queuing theory model, we propose a service decision mechanism based on the anticipated traffic flow. The proposed service decision mechanism aims to reduce the average waiting time of vehicles for service. Particularly, the RSUs will ask the Macro Base Station (MBS) for assistance when there are too many vehicles traveling through the RSUs. Finally, we conduct comprehensive experiments using real data to evaluate the model performance, and it is demonstrated that our proposed scheme outperforms other benchmarks. © 2023 IEEE.

关键词： Internet of Vehicles queuing theory service decision mechanism traffic flow prediction

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A Fault Diagnostic Method for Rolling Bearings Based on CAR-SNN Model

A Fault Diagnostic Method for Rolling Bearings Based on CAR-...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Li, Qiuting Wang, Xiuqing Du, Wenxia Hebei Normal University College of Computer and Cyber Security Shijiazhuang050024 China Hebei Provincial Key Laboratory of Network & Information Security Shijiazhuang China Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security Shijiazhuang China Hebei Normal University College of China Combustion Engineering Shijiazhuang050024 China

ISBN: (纸本)9798350337754

In the era of big data, high-performance rolling bearing fault diagnostic methods are of great significance to ensure manufacturing smoothly and avoid mass economic losses. A rolling bearing fault diagnostic CAR-SNN model based on Convolutional Block Attention Module (CBAM), Residual Network (ResNet), and Spiking Neural Networks (SNNs) is proposed based on deep learning (DL). The CAR-SNN model combines CBAM, ResNet, and SNNs to extract critical features while avoiding gradient vanishing or explosion phenomena. The ability of the CAR-SNN model to process spatio-temporal information is improved by using SNNs that incorporate spatio-temporal information simultaneously. The proposed model is used for the rolling bearing fault diagnosis, which datasets are from the experimental platforms of CWRU and Jiangnan University, with the highest diagnostic accuracy 99.995% and 99.18%, respectively. The experimental results validate the effectiveness and stability of the proposed model. The results of comparison experiments show that the CAR-SNN model has better fault diagnostic accuracy and stability than that of the CAR model and other comparison methods. The proposed data-driven rolling bearing fault diagnostic method based on the CAR-SNN model is easy to be implemented, and meeting the needs of high fault diagnostic accuracy in practical applications, and provides valuable input for fault diagnosis of rolling bearings. © 2023 IEEE.

关键词： Failure analysis

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Variable lanes traffic optimization control method combined with colorful asphalt materials 9

Variable lanes traffic optimization control method combined ...

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9th International Conference on Mechanical engineering, Materials, and Automation Technology, MMEAT 2023

作者： Wang, Ruihan Zhan, Xuejuan Liang, Zijun Li, Yuqi Xiao, Yun Peng, Min School of Urban Construction and Transportation Hefei University China Anhui Province Transportation Big Data Analysis and Application Engineering Laboratory China Key Laboratory of Traffic Information and Safety of Anhui Higher Education Institutes Anhui Sanlian University China

ISBN: (纸本)9781510668584

Along with our country's continuous growth, rising rush hours traffic congestion, many scholars proposed setting variable lanes solution, but due to the variable lanes different times the direction of the lane change, which made the driver can not be correctly into the right lane. So we propose a traffic optimization control method for variable lanes combined with colorful asphalt materials. Firstly, enumeration method is used to list all the direction schemes and phase schemes of the variable lanes, and the optimal scheme is obtained according to the constraints. In order to better distinguish the variable lanes from the conventional lanes, the variable lanes are paved with colorful asphalt environmental materials. Then the phase timing is calculated according to the determined variable lanes, phase scheme and traffic flow. Finally, through VISSIM traffic simulation software to evaluate the results, the results show that combining with colorful asphalt materials clearly calibrate the position of the variable lanes, effective rule on the variable lanes traffic space, and on this basis, through phase timing optimization technology to further improve the intersection traffic efficiency, effectively alleviate the intersection rush hours traffic congestion. It provides a basis for the research of variable lanes optimization control combined with colorful asphalt materials. © 2023 SPIE.

关键词： Traffic congestion

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knowledge Representation and Reasoning for Complex Time Expression in Clinical Text

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data Intelligence 2022年第3期4卷 573-598页

作者： Danyang Hu Meng Wang Feng Gao Fangfang Xu Jinguang Gu School of Computer Science and Technology Wuhan University of Science and TechnologyWuhan 430065China Key Laboratory of Rich-Media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration of the People’s Republic of ChinaBeijing 10038China Institute of Big Data Science and Engineering Wuhan University of Science and TechnologyWuhan 430065China

Temporal information is pervasive and crucial in medical records and other clinical text,as it formulates the development process of medical conditions and is vital for clinical decision ***,providing a holistic knowledge representation and reasoning framework for various time expressions in the clinical text is *** order to capture complex temporal semantics in clinical text,we propose a novel Clinical Time Ontology(CTO)as an extension from OWL *** specifically,we identified eight timerelated problems in clinical text and created 11 core temporal classes to conceptualize the fuzzy time,cyclic time,irregular time,negations and other complex aspects of clinical ***,we extended Allen’s and TEO’s temporal relations and defined the relation concept description between complex and simple ***,we provided a formulaic and graphical presentation of complex time and complex time *** carried out empirical study on the expressiveness and usability of CTO using real-world healthcare ***,experiment results demonstrate that CTO could faithfully represent and reason over 93%of the temporal expressions,and it can cover a wider range of time-related classes in clinical domain.

关键词： Clinical text Temporal ontology Temporal relations OWL Negation of temporal relation

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