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Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 932-945页

作者： Bin Yang Yaguo Lei Xiang Li Naipeng Li Asoke K.nandi the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System the School of Mechanical EngineeringXi’an Jiaotong UniveristyXi’an 710049 the Hunan Provincial Key Labortory of Health Maintenance for Mechanical Equipment Hunan Univeristy of Science and TechnologyXiangtan 411201China the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniveristyXi’an 710049China the Department of Electronic and Electrical Engineering Brunel University LondonUxbridge UB83PHUK

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source ***,in engineering scenarios,achieving such high-quality label annotation is difficult and *** incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled *** overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three ***,a residual network with dual classifiers is to learn features from cross-domain ***,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source *** the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised ***,the adaptation trajectories are designed for sample distributions across *** ensures that the target domain samples are only adapted with the pure-labeled *** LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related *** results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

关键词： Deep transfer learning domain adaptation incorrect label annotation intelligent fault diagnosis rotating machines

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Uncertainty-Aware Deep Learning: A Promising Tool for Trustworthy Fault Diagnosis

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1317-1330页

作者： Jiaxin Ren Jingcheng Wen Zhibin Zhao Ruqiang Yan Xuefeng Chen Asoke K.nandi School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China Department of Electronic and Electrical Engineering Brunel University LondonKingston LaneUxbridgeUB83PHUK IEEE

Recently,intelligent fault diagnosis based on deep learning has been extensively investigated,exhibiting state-of-the-art ***,the deep learning model is often not truly trusted by users due to the lack of interpretability of“black box”,which limits its deployment in safety-critical applications.A trusted fault diagnosis system requires that the faults can be accurately diagnosed in most cases,and the human in the deci-sion-making loop can be found to deal with the abnormal situa-tion when the models *** this paper,we explore a simplified method for quantifying both aleatoric and epistemic uncertainty in deterministic networks,called *** SAEU,Multivariate Gaussian distribution is employed in the deep architecture to compensate for the shortcomings of complexity and applicability of Bayesian neural *** on the SAEU,we propose a unified uncertainty-aware deep learning framework(UU-DLF)to realize the grand vision of trustworthy fault ***,our UU-DLF effectively embodies the idea of“humans in the loop”,which not only allows for manual intervention in abnor-mal situations of diagnostic models,but also makes correspond-ing improvements on existing models based on traceability ***,two experiments conducted on the gearbox and aero-engine bevel gears are used to demonstrate the effectiveness of UU-DLF and explore the effective reasons behind.

关键词： Out-of-distribution detection traceability analysis trustworthy fault diagnosis uncertainty quantification.

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Rectangular Microstrip Antenna with Air Cavity for High Gain and Improved Front to Back Ratio

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Journal of Electromagnetic Analysis and Applications 2011年第9期3卷 368-372页

作者： Kaushik Malakar jaydeep nandi Souvik Mitra Prasanta Kumar Gorai Sudipta Chattopadhyay Sandip Banerjee 不详

A rectangular microstrip patch antenna using conventional Poly Tetra Fluride Ethelene (PTFE) substrate with air cavity is proposed and theoretically investigated. Considerably high gain along with improved front to back radiation isolation is demonstrated using such proposed antenna. The radiation performance of this new antenna has been compared to a conventional microstrip patch for some commonly used aspect ratios (width to length ratio). Compared to conventional microstrip antenna the proposed configuration shows more than 12% increment in peak gain and more than 10% increment in front to back radiation performance in each set of aspect ratio. The elucidation of such improvement in the radiation characteristics of the proposed antenna is also presented.

关键词： Air Cavity Front to Back Radiation High Gain Microstrip Antenna

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Investigation on FBG based optical sensor for pressure and temperature measurement in civil application

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Optoelectronics Letters 2024年第9期20卷 531-536页

作者： Somesh nandi Chethana K T Srinivas Preeta Sharan Department of Artificial Intelligence and Machine Learning Rashtreeya Vidyalaya College of Engineering Department of Electronics and Communications Jyothy Institute of Technology Department of Electrical Communication Engineering Indian Institute of Science Department of Electronics and Communications the Oxford College of Engineering

Optical fiber Bragg grating(FBG) sensors have advanced significantly in the last several years. The use of innovative FBG in temperature and pressure measurement is examined in this study. The benefits of FBGs, such as their compact size, low weight, resilience to corrosion, immunity to electromagnetic interference, distributed sensing, and remote monitoring, have brought attention to the growing research in this field of structural health monitoring of civil infrastructures.

关键词： A

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基于地理探测器的元阳梯田地质灾害影响因素及滑坡成因分析

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中国地质调查 2024年第3期11卷 92-100页

作者：苏航卢楠迪伏小双李奇云南省有色地质局三O八队云南昆明650200

元阳梯田受其特殊的地理位置、地表植被和农耕文化影响,表生地质灾害频发,对其生态价值和文化价值造成极大损害,梯田区域的地质灾害防治显得尤为关键。在详细野外调查基础上,结合元阳梯田区15 m分辨率遥感影像数据,利用空间叠加分析和... 详细信息

元阳梯田受其特殊的地理位置、地表植被和农耕文化影响,表生地质灾害频发,对其生态价值和文化价值造成极大损害,梯田区域的地质灾害防治显得尤为关键。在详细野外调查基础上,结合元阳梯田区15 m分辨率遥感影像数据,利用空间叠加分析和地理探测器模型对研究区地质灾害影响因素开展了详细研究。结果表明:元阳梯田区地质灾害(隐患)点中滑坡灾害(隐患)点数量占比为93.39%,小型规模灾害(隐患)点数量占比为87.69%,总体表现为以滑坡性质的小型灾害为主;地质灾害分布的影响因素主要为地形坡度,其次为地质构造,受地貌单元影响最弱;滑坡灾害形成的影响因素具有复合性特点,其中强烈的河流侵蚀作用、地壳抬升作用和活跃的断裂构造活动是其成灾的主要地质环境背景,丰富的降雨量和人类工程活动是其成灾的主要触发因素。通过研究可进一步认识元阳梯田地质灾害影响因素及形成条件,可更好地助力于地方防灾减灾体系提升,也可为区域地质灾害风险分析提供一定的参考。

关键词：元阳梯田地质灾害地理探测器影响因素成因机制

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Ra数对停输管道原油相变特征的影响研究

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工程热物理学报 2024年第4期45卷 1055-1061页

作者：刘晓燕周正李从范玉泽张楠迪徐颖李晓庆东北石油大学机械科学与工程学院大庆163318 中国石油塔里木油田分公司库尔勒841000 常熟理工学院常熟215506

本文探究了Ra数对停输原油相变特征的影响,为管道停输时间控制提供参考依据。建立了基于焓法的原油相变传热数学模型,将固液模糊区处理为两相流区,利用格子Boltzmann方法求解原油相变传热控制方程组。将原油相变传热过程分为三个不同阶... 详细信息

本文探究了Ra数对停输原油相变特征的影响,为管道停输时间控制提供参考依据。建立了基于焓法的原油相变传热数学模型,将固液模糊区处理为两相流区,利用格子Boltzmann方法求解原油相变传热控制方程组。将原油相变传热过程分为三个不同阶段。发现Ra数对流场的影响会随时间不断减弱,对于凝油层的影响不断增强导致液相率场产生明显的形态变化。在换热第一阶段提高Ra数会使原油下沉速度的增长幅度远大于原油上升速度的增长幅度。

关键词：相变流动原油数值研究格子Boltzmann方法 Ra数

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混合现实全息影像技术在多种临床常用穿刺操作教学中的应用

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卫生职业教育 2024年第8期42卷 75-79页

作者：徐艺瑄魏星包楠迪解放军总医院第二医学中心北京100853 解放军总医院第六医学中心心血管病医学部北京100037

为评价混合现实全息影像技术在实习医师胸腔、腹腔、腰椎、骨髓穿刺操作教学中的应用价值,以解放军总医院2023年招收的实习医师为研究对象,随机分为实验组和对照组,实验组采用混合现实全息影像技术教学方法,对照组采用传统模具教学方法... 详细信息

为评价混合现实全息影像技术在实习医师胸腔、腹腔、腰椎、骨髓穿刺操作教学中的应用价值,以解放军总医院2023年招收的实习医师为研究对象,随机分为实验组和对照组,实验组采用混合现实全息影像技术教学方法,对照组采用传统模具教学方法,进行胸腔、腹腔、腰椎、骨髓穿刺操作教学,并通过考试及教学满意度问卷调查比较两组教学效果的差异。实践表明,混合现实全息影像技术教学方法在胸腔、腹腔、腰椎、骨髓穿刺操作教学中应用,收到满意的教学效果,且实习医师教学满意度高。

关键词：混合现实技术全息影像穿刺操作教学

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前蛋白转化酶枯草溶菌素9抑制剂的临床研究及应用进展

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中华老年多器官疾病杂志 2024年第4期23卷 311-315页

作者：赵瑾陈鹏飞包楠迪中国人民解放军总医院京北医疗区红山口门诊部北京100091 中国人民解放军总医院第六医学中心心血管病医学部北京100853

前蛋白转化酶枯草溶菌素9(PCSK9)抑制剂可通过抑制肝细胞表面低密度脂蛋白受体的降解对脂质代谢起到调节作用。目前已有多项临床研究证明,PCSK9抑制剂单一药物或与他汀类药物联合使用可显著降低低密度脂蛋白胆固醇水平。本文综述了当前P... 详细信息

前蛋白转化酶枯草溶菌素9(PCSK9)抑制剂可通过抑制肝细胞表面低密度脂蛋白受体的降解对脂质代谢起到调节作用。目前已有多项临床研究证明,PCSK9抑制剂单一药物或与他汀类药物联合使用可显著降低低密度脂蛋白胆固醇水平。本文综述了当前PCSK9抑制剂的重要临床研究及应用进展,并简要总结了常见PCSK9抑制剂的安全性、有效性及临床应用现状。

关键词：前蛋白转化酶枯草溶菌素9 低密度脂蛋白胆固醇脂质代谢动脉粥样硬化

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Systematic bio‑fabrication of aptamers and their applications in engineering biology

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Systems Microbiology and Biomanufacturing 2023年第2期3卷 223-245页

作者： Rongfeng Cai Xin Chen Yuting Zhang Xiaoli Wang nandi Zhou The Key Laboratory of Carbohydrate Chemistry and Biotechnology Ministry of EducationSchool of BiotechnologyJiangnan UniversityWuxi 214122China

Aptamers are single-stranded DNA or RNA molecules that have high affinity and selectivity to bind to specific *** to antibodies,aptamers are easy to in vitro synthesize with low cost,and exhibit excellent thermal stability and *** these features,aptamers have been widely used in biology and medicine-related *** the meantime,a variety of systematic evolution of ligands by exponential enrichment(SELEX)technologies have been developed to screen aptamers for various *** to the characteristics of targets,customizing appropriate SELEX technology and post-SELEX optimization helps to obtain ideal aptamers with high affinity and *** this review,we first summarize the latest research on the systematic bio-fabrication of aptamers,including various SELEX technologies,post-SELEX optimization,and aptamer modification *** procedures not only help to gain the aptamer sequences but also provide insights into the relationship between structure and function of the *** latter provides a new perspective for the systems bio-fabrication of ***,on this basis,we review the applications of aptamers,particularly in the fields of engineering biology,including industrial biotechnology,medical and health engineering,and environmental and food safety *** the encountered challenges and prospects are discussed,providing an outlook for the future development of aptamers.

关键词： Aptamer SELEX Engineering biology Biosensors

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Scale‐wise interaction fusion and knowledge distillation network for aerial scene recognition

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1178-1190页

作者： Hailong Ning Tao Lei Mengyuan An Hao Sun Zhanxuan Hu Asoke K.nandi School of Computer Science and Technology Xi'an University of Posts and TelecommunicationsShaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'anChina Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'anChina School of Electronic Information and Artificial Intelligence Shaanxi University of Science and TechnologyXi'anChina School of Computer Central China Normal UniversityWuhanChina Department of Electronic and Electrical Engineering Brunel University LondonLondonUK Xi'an Jiaotong University Xi'anChina

Aerial scene recognition(ASR)has attracted great attention due to its increasingly essential *** of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ***,the existing multi‐scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features,leading to a limited ability to deal with challenges of large‐scale variation and complex background in aerial scene *** addition,existing methods may suffer from poor generalisations due to millions of to‐belearnt parameters and inconsistent predictions between global and local *** tackle these problems,this study proposes a scale‐wise interaction fusion and knowledge distillation(SIF‐KD)network for learning robust and discriminative features with scaleinvariance and background‐independent *** main highlights of this study include two *** the one hand,a global‐local features collaborative learning scheme is devised for extracting scale‐invariance features so as to tackle the large‐scale variation problem in aerial scene ***,a plug‐and‐play multi‐scale context attention fusion module is proposed for collaboratively fusing the context information between global and local *** the other hand,a scale‐wise knowledge distillation scheme is proposed to produce more consistent predictions by distilling the predictive distribution between different scales during *** experimental results show the proposed SIF‐KD network achieves the best overall accuracy with 99.68%,98.74%and 95.47%on the UCM,AID and NWPU‐RESISC45 datasets,respectively,compared with state of the arts.

关键词： deep learning image analysis image classification information fusion

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