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A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

Machine Intelligence Research 2024年第1期21卷 153-168页

作者： Zefa Hu Ziyi Ni jing shi Shuang Xu Bo Xu School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative ***,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each *** paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above *** task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated *** this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status ***,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource *** experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings.

关键词： Medical dialogue understanding information extraction text generation knowledge-enhanced prompt low-resource setting dataaugmentation

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Global-local combined features to detect pain intensity from facial expression images with attention mechanism

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Journal of Electronic Science and Technology 2024年第3期22卷 80-93页

作者： Jiang Wu Yi shi Shun Yan hong-Mei Yan Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313001China MOE Key Laboratory for Neuroinformation School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu611731China College of Engineering University of California at Santa BarbaraSanta Barbara93106USA

The estimation of pain intensity is critical for medical diagnosis and treatment of *** the development of image monitoring technology and artificial intelligence,automatic pain assessment based on facial expression and behavioral analysis shows a potential value in clinical *** paper reports a framework of convolutional neural network with global and local attention mechanism(GLA-CNN)for the effective detection of pain intensity at four-level thresholds using facial expression ***-CNN includes two modules,namely global attention network(GANet)and local attention network(LANet).LANet is responsible for extracting representative local patch features of faces,while GANet extracts whole facial features to compensate for the ignored correlative features between *** the end,the global correlational and local subtle features are fused for the final estimation of pain *** under the UNBC-McMaster Shoulder Pain database demonstrate that GLA-CNN outperforms other state-of-the-art ***,a visualization analysis is conducted to present the feature map of GLA-CNN,intuitively showing that it can extract not only local pain features but also global correlative facial *** study demonstrates that pain assessment based on facial expression is a non-invasive and feasible method,and can be employed as an auxiliary pain assessment tool in clinical practice.

关键词： Attention Convolutional neural network Facial expression Pain intensity

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Improving RSW nugget diameter prediction method:unleashing the power of multi-fidelity neural networks and transfer learning

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Advances in Manufacturing 2024年第3期12卷 409-427页

作者： Zhong-Jie Yue Qiu-Ren Chen Zu-Guo Bao Li Huang Guo-Bi Tan Ze-hong Hou Mu-shi Li shi-Yao Huang Hai-Long Zhao jing-Yu Kong Jia Wang Qing Liu Key Laboratory for Light-weight Materials Nanjing Tech UniversityNanjing210009People’s Republic of China School of Advanced Technology Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuPeople’s Republic of China Material Academy JITRISuzhou215100JiangsuPeople’s Republic of China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

This research presents an innovative approach to accurately predict the nugget diameter in resistance spot welding(RSW)by leveraging machine learning and transfer learning ***,low-fidelity(LF)data were obtained through finite element numerical simulation and design of experiments(DOEs)to train the LF machine learning ***,high-fidelity(HF)data were collected from RSW process experiments and used to fine-tune the LF model by transfer learning *** accuracy and generalization performance of the models were thoroughly *** results demonstrated that combining different fidelity datasets and employing transfer learning could significantly improve the prediction accuracy while minimize the costs associated with experimental trials,and provide an effective and valuable method for predicting critical process parameters in RSW.

关键词： Resistance spot welding(RSW) Nugget diameter prediction Multi-fidelity neural networks Transfer learning

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Research on intelligent search-and-secure technology in accelerator hazardous areas based on machine vision

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Nuclear Science and Techniques 2024年第4期35卷 96-107页

作者： Ying-Lin Ma Yao Wang hong-Mei shi Hui-Jie Zhang School of Traffic and Transportation Beijing Jiaotong UniversityBeijing 100044China School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China

Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to ***,manual sweep methods are ***,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale *** leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and *** the criticality of personal safety for stranded individuals,search and security processes must be sufficiently *** ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring *** YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the ***,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive *** strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall ***,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,*** there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software *** tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.

关键词： Search and secure Machine vision Camera Human body parts recognition Particle accelerator Hazardous area

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Interfacial fusion-enhanced 11 μm-thick gel polymer electrolyte for high-performance lithium metal batteries

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Journal of Energy Chemistry 2024年第11期 58-66页

作者： Ying Jiang Xinyue hong Peng Huang jing shi Wen Yan Chao Lai School of Chemistry and Materials Science Jiangsu Normal University

In the pursuit of ultrathin polymer electrolyte（<20 μm） for lithium metal batteries, achieving a balance between mechanical strength and interfacial stability is crucial for the longevity of the ***, 11 μm-thick gel polymer electrolyte is designed via an integrated electrode/electrolyte structure supported by lithium metal anode. Benefiting from an exemplary superiority of excellent mechanical property, high ionic conductivity, and robust interfacial adhesion, the in-situ formed polymer electrolyte reinforced by titanosiloxane networks（ISPTS） embodies multifunctional roles of physical barrier, ionic carrier, and artificial protective layer at the interface. The potent interfacial interactions foster a seamless fusion of the electrode/electrolyte interfaces and enable continuous ion transport. Moreover, the built-in ISPTS electrolyte participates in the formation of gradient solid-electrolyte interphase（SEI） layer, which enhances the SEI's structural integrity against the strain induced by volume fluctuations of lithium ***, the resultant 11 μm-thick ISPTS electrolyte enables lithium symmetric cells with cycling stability over 600 h and LiFePO4cells with remarkable capacity retention of 96.6% after 800 *** study provides a new avenue for designing ultrathin polymer electrolytes towards stable, safe,and high-energy–density lithium metal batteries.

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Predicting submerged vegetation drag with a machine learning-based method

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Journal of Hydrodynamics 2024年第3期36卷 534-545页

作者： Meng-yang Liu hong-wu Tang Sai-yu Yuan jing Yan College of Water Conservancy and Hydropower Engineering Hohai UniversityNanjing210098China Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources Hohai UniversityNanjing210098China

Accurate estimation of the drag forces generated by vegetation stems is crucial for the comprehensive assessment of the impact of aquatic vegetation on hydrodynamic processes in aquatic *** coupling relationship between vegetation layer flow velocity and vegetation drag makes precise prediction of submerged vegetation drag forces particularly *** present study utilized published data on submerged vegetation drag force measurements and employed a genetic programming(GP)algorithm,a machine learning technique,to establish the connection between submerged vegetation drag forces and flow and vegetation *** using the bulk velocity,U,as the reference velocity scale to define the drag coefficient,C_(d),and stem Reynolds number,the GP runs revealed that the drag coefficient of submerged vegetation is related to submergence ratio(H^(*)),aspect ratio(d^(*)),blockage ratio(ψ^(*)),and vegetation density(λ).The relation between vegetation stem drag forces and flow velocity is implicitly embedded in the definition of C_(d).Comparisons with experimental drag force measurements indicate that using the bulk velocity as the reference velocity,as opposed to using the vegetation layer average velocity,U_(v),eliminates the need for complex iterative processes to estimate U_(v)and avoids introducing additional errors associated with U_(v)*** approach significantly enhances the model’s predictive capabilities and results in a simpler and more user-friendly formula expression.

关键词： Drag coefficient genetic programming algorithm submerged vegetation flow resistance cylinder array

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A Cauchy integral formula for(p,q)-monogenic functions withα-weight

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Applied Mathematics(A Journal of Chinese Universities) 2024年第3期39卷 545-553页

作者： GAO Long DU Xiao-jing LIU Yue XIE Yong-hong School of Mathematical Sciences Hebei Normal UniversityShijiazhuang 050024China

Firstly,some properties for(p,q)-monogenic functions withα-weight in Clifford analysis are ***,the Cauchy-Pompeiu formula is ***,the Cauchy integral formula and the Cauchy integral theorem for(p,q)-monogenic function... 详细信息

关键词： (p q)-monogenic functions with-weight Cauchy-Pompeiu formula Cauchy integral formula Cauchy integral theorem

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Differential Game Model of Resource Extraction with Continuous and Dynamic Updating

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Journal of the Operations Research Society of China 2024年第1期12卷 51-75页

作者： Ovanes Petrosian Tihomirov Denis Jiang-jing Zhou hong-Wei Gao School of Mathematics Harbin Institute of TechnologyHarbin150001HeilongjiangChina School of Automation Qingdao UniversityQingdao266071ShandongChina Faculty of Applied Mathematics and Control Processes Saint-Petersburg State UniversitySaint PetersburgRussia National Research University"High School of Economics" Saint-PetersburgRussia School of Mathematics and Statistics Qingdao UniversityQingdao266071ShandongChina

This paper is devoted to a new class of differential games with continuous and dynamic *** direct application of resource extraction in a case of dynamic and continuous updating is *** is proved that the optimal control(cooperative strategies)and feedback Nash equilibrium strategies uniformly converge to the corresponding strategies in the game model with continuous updating as the number of updating instants converges to *** results are presented for an optimal trajectory(cooperative trajectory),equilibrium trajectory and corresponding payoffs.

关键词： Differential games Dynamic updating Continuous updating Optimal control Feedback Nash equilibrium

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Prediction and interpretation of photocatalytic NO removal on g-C_(3)N_(4)-based catalysts using machine learning

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Chinese Chemical Letters 2024年第2期35卷 477-483页

作者： jing Li Xinyan Liu hong Wang Yanjuan Sun Fan Dong School of Resources and Environment University of Electronic Science and Technology of ChinaChengdu 611731China Research Center for Carbon-Neutral Environmental & Energy Technology Institute of Fundamental and Frontier SciencesUniversity of Electronic Science and Technology of ChinaChengdu 611731China

Predictive modeling of photocatalytic NO removal is highly desirable for efficient air pollution ***,great challenges remain in precisely predicting photocatalytic performance and understanding interactions of diverse features in the catalytic ***,a dataset of g-C_(3) N_(4)-based catalysts with 255 data points was collected from peer-reviewed publications and machine learning(ML)model was proposed to predict the NO removal *** result shows that the Gradient Boosting Decision Tree(GBDT)demonstrated the greatest prediction accuracy with R 2 of 0.999 and 0.907 on the training and test data,*** SHAP value and feature importance analysis revealed that the empirical categories for NO removal rate,in the order of importance,were catalyst characteristics>reaction process>preparation ***,the partial dependence plots broke the ML black box to further quantify the marginal contributions of the input features(e.g.,doping ratio,flow rate,and pore volume)to the model output *** ML approach presents a pure data-driven,interpretable framework,which provides new insights into the influence of catalyst characteristics,reaction process,and preparation conditions on NO removal.

关键词： Machine learning g-C_(3)N_(4)-based catalysts NO removal Interpretability Catalytic informatics

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PDOL-Based Solid Electrolyte Toward Practical Application:Opportunities and Challenges

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Nano-Micro Letters 2024年第7期16卷 109-141页

作者： Hua Yang Maoxiang jing Li Wang hong Xu Xiaohong Yan Xiangming He Institute for Advanced Materials School of Materials Science and EngineeringJiangsu UniversityZhenjiang 212013People’s Republic of China Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084People’s Republic of China

Polymer solid-state lithium batteries(SSLB)are regarded as a promising energy storage technology to meet growing demand due to their high energy density and *** conductivity,interface stability and battery assembly process are still the main challenges to hurdle the commercialization of *** the main component of SSLB,poly(1,3-dioxolane)(PDOL)-based solid polymer electrolytes polymerized in-situ are becoming a promising candidate solid elec-trolyte,for their high ion conductivity at room temperature,good battery elec-trochemical performances,and simple assembly *** review analyzes opportunities and challenges of PDOL electrolytes toward practical application for polymer *** focuses include exploring the polymerization mechanism of DOL,the performance of PDOL composite electrolytes,and the application of ***,we provide a perspective on future research directions that need to be emphasized for commercialization of PDOL-based electrolytes in *** exploration of these schemes facilitates a comprehensive and profound understanding of PDOL-based polymer electrolyte and provides new research ideas to boost them toward practical application in solid-state batteries.

关键词： Poly(1,3-dioxolane) Solid electrolyte Polymerization mechanism Composite electrolyte Practical application

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