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Ultra-high temperature shape memory in high-Hf content NiTiHf alloys

材料科学技术（英文版） 2025年第6期209卷 124-127页

作者： A.V.Shuitcev Q.Z.Li M.G.Khomutov L Li Y.X.Tong International Joint Laboratory of Advanced Nanomaterials of Heilongjiang Province College of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin150001China National University of Science and Technology"MISIS" Moscow119049Russia

The active development of space industry necessitates the cre-ation of novel materials with unique properties,including shape memory alloys(SMAs).The development of ultra-high temperature SMAs(UHTSMAs)with operating temperatures above 400 ℃ is a significant challenge[1-3].It is known that reversible thermoelas-tic martensitic transformation(MT)is the basis for shape mem-ory behavior[4].Currently,there are several systems in which MT temperatures meet the above requirements,for example,RuNb[5],HfPd[6],TiPd[7],TiPt[8],TiNiPd[9],TiNiPt[10],NiTiHf[11],*** them,NiTiHf alloys are of particular interest due to the following ***,Hf significantly increases MT tempera-tures of NiTi-based alloys[2].Secondly,these alloys exhibit high dimensional stability and high work output(up to～250 ℃)[12].Thirdly,they are relatively inexpensive in comparison with other *** operating temperatures may be an unfavorable fac-tor influencing the reversible strain *** thermoelastic na-ture of MT requires the elastic stresses that arise during the crys-tallographic rearrangements of high-temperature austenite phase into low-temperature martensite to be *** relax-ation processes at elevated temperatures can be particularly active,which may suppress strain recovery.

关键词： temperature content memory shape alloys high-hf nitihf ultra-high

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Formal Modeling and Discovery of Multi-instance Business Processes: A Cloud Resource Management Case Study

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2151-2160页

作者： Cong Liu IEEE School of Computer Science and Technology Shandong University of TechnologyZibo 255000 College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China

Process discovery, as one of the most challenging process analysis techniques, aims to uncover business process models from event logs. Many process discovery approaches were invented in the past twenty years;however, most of them have difficulties in handling multi-instance sub-processes. To address this challenge, we first introduce a multi-instance business process model(MBPM) to support the modeling of processes with multiple sub-process instantiations. Formal semantics of MBPMs are precisely defined by using multi-instance Petri nets(MPNs)that are an extension of Petri nets with distinguishable ***, a novel process discovery technique is developed to support the discovery of MBPMs from event logs with sub-process multi-instantiation information. In addition, we propose to measure the quality of the discovered MBPMs against the input event logs by transforming an MBPM to a classical Petri net such that existing quality metrics, e.g., fitness and precision, can be *** proposed discovery approach is properly implemented as plugins in the Pro M toolkit. Based on a cloud resource management case study, we compare our approach with the state-of-theart process discovery techniques. The results demonstrate that our approach outperforms existing approaches to discover process models with multi-instance sub-processes.

关键词： Cloud resource management process multi-instance Petri nets(MPNs) multi-instance sub-processes process discovery quality evaluation

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RT-YOLO:A Residual Feature Fusion Triple Attention Network for Aerial Image Target Detection

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computers, Materials & Continua 2023年第4期75卷 1411-1430页

作者： Pan Zhang Hongwei Deng Zhong Chen College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China

In recent years,target detection of aerial images of unmannedaerial vehicle(UAV)has become one of the hottest ***,targetdetection of UAV aerial images often presents false detection and *** proposed a modified you only look once(YOLO)model toimprove the problems arising in object detection in UAV aerial images:(1)A new residual structure is designed to improve the ability to extract featuresby enhancing the fusion of the inner features of the single *** the sametime,triplet attention module is added to strengthen the connection betweenspace and channel and better retain important feature information.(2)Thefeature information is enriched by improving the multi-scale feature pyramidstructure and strengthening the feature fusion at different scales.(3)A newloss function is created and the diagonal penalty term of the anchor frame isintroduced to improve the speed of training and the accuracy of *** proposed model is called residual feature fusion triple attention YOLO(RT-YOLO).Experiments showed that the mean average precision(mAP)ofRT-YOLO is increased from 57.2%to 60.8%on the vehicle detection in aerialimage(VEDAI)dataset,and the mAP is also increased by 1.7%on the remotesensing object detection(RSOD)*** results show that theRT-YOLOoutperforms other mainstream models in UAV aerial image object detection.

关键词： Attention mechanism small target detection YOLOv5s RT-YOLO

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PiCNet: Physics-infused Convolution Network for Radar-Based Precipitation Nowcasting

PiCNet: Physics-infused Convolution Network for Radar-Based ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Wang, Zheng Zhang, Hanyi Bai, Cong College of Computer Science and Technology Zhejiang University of Technology China

ISBN: (纸本)9798350368741

Meteorological disasters, especially extreme precipitation, cause significant socioeconomic damage, highlighting the need for effective quantitative precipitation nowcasting. Existing methods, often data-driven and resource-intensive, struggle to capture the underlying physical laws of meteorology. This paper introduces a simple yet effective model using an advection simulator to learn precipitation's physical dynamics, making the predictions more interpretable. Our model also incorporates a physics-guided module to enhance sensitivity to high-intensity rainfall, improving rainfall prediction accuracy. Experiments on the KNMI radar echo dataset demonstrate that our model outperforms state-of-the-art methods, offering better insights into physics-infused precipitation nowcasting. © 2025 IEEE.

关键词： High-intensity rainfall Physics-infused method Precipitation nowcasting

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Eyes on Islanded Nodes: Better Reasoning via Structure Augmentation and Feature Co-Training on Bi-Level Knowledge Graphs

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IEEE Transactions on Image Processing 2025年 34卷 3268-3280页

作者： Li, Hao Liang, Ke Yang, Wenjing Meng, Lingyuan Wang, Yaohua Zhou, Sihang Liu, Xinwang National University of Defense Technology School of Computer Changsha410073 China National University of Defense Technology College of Intelligence Science and Technology Changsha410073 China

Knowledge graphs (KGs) represent known entities and their relationships using triplets, but this method cannot represent relationships between facts, limiting their expressiveness. Recently, the Bi-level Knowledge Graph (Bi-level KG) has addressed this issue by modeling facts as nodes and establishing relationships between these facts, introducing two new tasks: triplet prediction and conditional link prediction. Existing methods enhance triplets through data augmentation method and represent facts using entity representations. However, these methods do not address the isolated nodes at the structure level, nor do they effectively capture the information of facts at the feature level. To address these two issues, we design a data augmentation method that identifies islanded node by detecting anomalous structures and features in the graph. Subsequently, we perform similar subgraph matching for each isolated node to construct potential facts. To enrich the features of facts, we design a weighted combination initialization method for facts and introduce a new relation R˜ , to connect facts with related entities. This approach allows for the co-training of fact and entity representations during the training process. Extensive experiments validate the effectiveness of our data augmentation and co-training methods. Our model achieves optimal performance in triplet prediction and conditional link prediction tasks. © 1992-2012 IEEE.

关键词： Graphic methods

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Construction of Pressure Vessel Accident Emergency Drill System and Design of Scoring Mechanism based on Virtual Reality technology

Construction of Pressure Vessel Accident Emergency Drill Sys...

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2024 International Conference on Measurement, Communication, and Virtual Reality, MCVR 2024

作者： Wang, Xinmiao Ma, Dezhong Niu, Chenchen Han, Yichi Li, Zhichao College of Measurement-control Technology & Communications Engineering Harbin University of Science & Technology Harbin China Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781510691773

To address the issues of high risk, high cost, limited coverage, and low effectiveness in pressure vessel emergency drills, this study aims to construct a pressure vessel accident emergency drill system based on virtual reality technology. The system utilizes Unity3D to develop a human-computer interaction interface and implements various functional modules using C# scripting. The system incorporates features such as scenario simulation, safety education and training, interactive operations, multi-player collaboration, and feedback and evaluation, enabling drill participants to train and examine their emergency response skills within a virtual environment. To ensure the objectivity and comprehensiveness of the scoring system, this study employs a combined weighting method of the Entropy Weight Method and Analytic Hierarchy Process to analyze the weights of the operational steps in the exercise process. A comprehensive and objective scoring mechanism for the pressure vessel accident emergency exercise system has been designed, which evaluates the performance of the exercise personnel from multiple dimensions and levels. Furthermore, a comprehensive and objective rating mechanism for the emergency drill system of pressure vessels was designed to evaluate the performance of the drill personnel from multiple dimensions and hierarchical levels. This system effectively enhances participants' abilities in rapid response, emergency handling, and teamwork during accidents. © 2025 SPIE.

关键词： Virtual environments

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Advancing self-healing soy protein hydrogel with dynamic Schiff base and metal-ligand bonds for diabetic chronic wound recovery

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Aggregate 2024年第6期5卷 400-413页

作者： Tian Lan Yabo Dong Jiajia Shi Xing Wang Zejian Xu Yan Zhang Lianzhou Jiang Weibiao Zhou Xiaonan Sui College of Food Science Northeast Agricultural UniversityHarbinChina College of Horticulture and Landscape Architecture Northeast Agricultural UniversityHarbinChina Department of Food Science and Technology National University of SingaporeSingaporeSingapore

To address the unique challenges of diabetic wound healing,wound dressings,particularly multifunctional hydrogels have garnered considerable *** the first time,a novel environmentally friendly soy protein-based hydrogel is developed to accelerate the healing of diabetic chronic ***,this hydrogel framework is in direct formation through the dynamic Schiff base between oxidized guar gum and epigallocatechin-3-gallate(EGCG)-modified soy protein ***,the addition of Ag^(+)enhances the cross-linking of the hydrogel network by forming metal-ligand bonds with the catechol groups in ***,the stretchability(up to 380%),swelling,and rheology properties of the hydrogel can be controlled by fine-tuning the density of metal-ligand bonds,endowing them with a high potential for precise ***,various dynamic bonds endow hydrogel with excellent self-healing ability,adhesiveness,and *** hydrogel also exhibits good antibacterial properties,biocompatibility,and cell migration *** in vivo and in vitro experiments demonstrated the outstanding anti-inflammatory capacity of the hydrogel and its ability to modulate macrophage ***,the hydrogel has proven effective in promoting wound healing in a diabetic full-thickness wound model through enhanced angiogenesis and collagen *** eco-friendly plant protein hydrogel offers a sustainable solution for wound care and environmental protection.

关键词： antibacterial anti-inflammatory diabetes chronic wounds self-healing soy protein based-hydrogel

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Efficient Structure Slimming for Spiking Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 3823-3831页

作者： Li, Yaxin Fang, Xuanye Gao, Yuyuan Zhou, Dongdong Shen, Jiangrong Liu, Jian K. Pan, Gang Xu, Qi Dalian University of Technology School of Computer Science and Technology Dalian116024 China Zhejiang University College of Computer Science and Technology Zhejiang310027 China University of Birmingham College of Engineering and Physical Sciences BirminghamB152TT United Kingdom

Spiking neural networks (SNNs) are deeply inspired by biological neural information systems. Compared to convolutional neural networks (CNNs), SNNs are low power consumption because of their spike based information processing mechanism. However, most of the current structures of SNNs are fully connected or converted from deep CNNs which poses redundancy connections. While the structure and topology in human brain systems are sparse and efficient. This article aims at taking full advantage of sparse structure and low power consumption which lie in human brain and proposed efficient structure slimming methods. Inspired by the development of biological neural network structures, this article designed types of structure slimming methods including neuron pruning and channel pruning. In addition to pruning, this article also considers the growth and development of the nervous system. Through iterative application of the proposed neural pruning and rewiring algorithms, experimental evaluations on Canadian Institute for Advanced Research (CIFAR)-10, CIFAR-100, and dynamic vision sensor (DVS)-gesture datasets demonstrate the effectiveness of the structure slimming methods. When the parameter count is reduced to only about 10% of the original, the performance decreases by less than 1%. © 2020 IEEE.

关键词： Energy efficiency

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Study on Dynamic Behavior of SF6/N2 Discharge Under Narrow-Gap Uniform Electric Field 7

Study on Dynamic Behavior of SF6/N2 Discharge Under Narrow-G...

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7th International Conference on Electric Power Equipment - Switching technology, ICEPE-ST 2024

作者： Wang, Yingli Cao, Dongyue Zhang, Mingquan Lu, Qiming Zheng, Dianchun College of Measurement and Communication Harbin University of Science and Technology Harbin China School of Electrical and Electronic Engineering Harbin University of Science and Technology Harbin China

ISBN: (纸本)9798350388947

In this paper, a hydrodynamic model of narrow-gap SF6/N2 gas discharge with flat electrode configuration was established, and the microscopic behavior characteristics of sulfur hexafluoride gas discharge under uniform electric field conditions were strictly studied, and the whole process of discharge triggering, generation of charged particles, particle adhesion, particle recombination, and evolution of discharge trajectory until gap breakdown was revealed. What's more, different discharge triggering conditions were further explored, and the influence mechanism of the initial seed electron density on the model discharge process was investigated in detail. The research results showed that the initial seed electron group density peak N0 was tightly correlated to the spatial charged particles, the gap electric field distribution, and the evolution of the discharge trajectory. Although the initial seed electron group position Z0 has a certain effect on the microscopic behavior of discharge, it is mainly reflected in the spatiotemporal scale of the streamer development process. © 2024 IEEE.

关键词： Electrons

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High Utility Periodic Frequent Pattern Mining in Multiple Sequences

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computer Modeling in Engineering & sciences 2023年第10期137卷 733-759页

作者： Chien-Ming Chen Zhenzhou Zhang Jimmy Ming-Tai Wu Kuruva Lakshmanna College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Technology Vellore Institute of TechnologyVellore632014India

Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic patternmining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodicpatterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequencesis more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences isimportant. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To addressexisting problems, three new measures are defined: the utility, high support, and high-utility period sequenceratios. Further, a new upper bound, upSeqRa, and two new pruning properties were proposed. MHUPFPS usesa newly defined HUPFPS-list structure to significantly accelerate the reduction of the search space and improvethe overall performance of the algorithm. Furthermore, the proposed algorithmis evaluated using several *** experimental results indicate that the algorithm is accurate and effective in filtering several non-high-utilityperiodic frequent patterns.

关键词： Decision making frequent periodic pattern multi-sequence database sequential rules utility mining

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