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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Singh, Swati Kumar, Shashi Ranjan Mukherjee, Dwaipayan Intelligent Systems and Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400 076 India Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai400 076 India

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article proposes a guidance scheme for stationary targets to achieve time-constrained interception at a desired time, considering the bounded field-of-view capability of seekerequipped interceptors and the physical limits of the actuator. Actuator saturation is a crucial problem in physical systems, often resulting in performance degradation. However, the actuator limitations are usually known to the designer, therefore, augmenting these constraints into the guidance design may enhance performance. The time-to-go error-based approach is used to satisfy the field-of-view constraint;further, the engagement kinematics are augmented with an input saturation model to incorporate the lateral acceleration constraints. Subsequently, the guidance strategy that constrains the lateral acceleration and the time-to-go values within their respective bounds is derived using Lyapunov stability concepts and the backstepping technique. Furthermore, a multi-stage approach is suggested to expand the achievable range of impact time. Numerical simulations are performed to validate the efficacy of the proposed scheme for different initial engagement geometries. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Backstepping

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A hybrid deep learning approach for phenotype prediction from clinical notes

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Journal of Ambient Intelligence and Humanized Computing 2023年第4期14卷 4503-4513页

作者： Khalafi, Sahar Ghadiri, Nasser Moradi, Milad Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Institute for Artificial Intelligence Center for Medical Statistics Informatics and Intelligent Systems Medical University of Vienna Vienna Austria

Identifying patient cohorts from clinical notes in secondary use of electronic health records is a fundamental task in clinical information management. The patient cohort identification process requires identifying the patient phenotypes. However, the growing number of clinical notes makes it difficult to analyze the data manually. Therefore, automatically extracting clinical concepts is crucial to identify patient phenotypes correctly. This paper’s proposed hybrid model is based on a neural bidirectional sequence model (BiLSTM or BiGRU) and a Convolutional Neural Network (CNN) for identifying patients’ phenotypes in clinical notes. Furthermore, an extra CNN layer is run parallel to the hybrid proposed model to extract more features related to each phenotype. We used pre-trained embeddings such as FastText and Word2vec separately as the input layers to evaluate other embedding’s performance in identifying patient phenotypes. We also measured the effect of adding additional data cleaning steps on discharge reports to identify patient phenotypes using deep learning models. Results demonstrated the proposed hybrid model extracts more features than existing methods of patient phenotype extraction and provides a better F1-score. We show that complementing the proposed hybrid model with an extra CNN in identifying different phenotypes improves the F1 scores. In addition, eliminating punctuation, numbers, and stop words in discharge reports before training hybrid models increased model performance. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Embeddings

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Additive manufacturing of high-quality tritium breeding pebbles using ceramic precursors

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Journal of the European Ceramic Society 2024年第7期44卷 4719-4730页

作者： Su, Fang Li, Yuzeng Xing, Huanhuan Liu, Yu Liu, Zhiyuan Liu, Changyong Jiang, Cho-Pei Chen, Zhangwei Additive Manufacturing Institute Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robotics Shenzhen University Shenzhen518060 China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an710049 China

In this study, the fabrication of advanced lithium orthosilicate (Li4SiO4) ceramic tritium breeding pebbles through photopolymerization using ceramic precursors (i.e., SiO2 and Li2CO3) is reported for the first time. The pebbles exhibit excellent mechanical and physical properties. Through optimization of manufacturing parameters and a geometrical correction model to compensate printing deviations, the printing accuracy of the pebbles was enhanced. The resulting pebbles had a diameter of approximately 1 mm, a sphericity of 1.01, a uniformly distributed pore structure, a phase purity > 95%, and a satisfying relative density reaching 91.39%. The average crush load 25.7 ± 0.3 N, surpassed that achieved by previously reported methods. Furthermore, the thermal conductivity was enhanced compared to that of solid-phase synthesized Li4SiO4 powder, facilitating the tritium release process for fusion applications. This study may serve as a guidance for designing appropriate ceramic breeders, providing a cost-effective approach applicable to produce other high-precision ceramic components with complex compositions. © 2024 Elsevier Ltd

关键词： Lithium compounds

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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhou 310018ZhejiangChina

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet

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Computer systems Science & engineering 2023年第9期46卷 2741-2754页

作者： Sana Zahir Rafi Ullah Khan Mohib Ullah Muhammad Ishaq Naqqash Dilshad Amin Ullah Mi Young Lee Institute of Computer Sciences and Information Technology(ICS/IT) The University of AgriculturePeshawar25130Khyber PakhtunkhwaPakistan Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Collaborative Robotics and Intelligent Systems(CoRIS)Institute Oregon State UniversityORUSA Department of Software Sejong UniversitySeoul05006Korea

The analysis of overcrowded areas is essential for flow monitoring,assembly control,and *** counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary *** crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test *** this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd *** proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training *** decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive *** benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models.

关键词： Artificial intelligence deep learning crowd counting scene understanding

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Development of a High-Frequency Power Source Dedicated to DBD Reactors for Ozone Production 3

Development of a High-Frequency Power Source Dedicated to DB...

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3rd International Conference on Advanced electrical engineering, ICAEE 2024

作者： Bechekir, Seyf Eddine Belabed, Meriem Brahami, Mostefa Jbilou, Mokhtaria Nemmich, Said Marref, Mohemed Amine Djillali Liabes University of Sidi Bel-Abbes Intelligent Control and Electrical Power Systems Laboratory Department of Electrical Engineering Algeria Algeria Djillali Liabes University of Sidi Bel-Abbes Intelligent Control and Electrical Power Systems Laboratory Algeria Institute of Applied Sciences and Technologies University of Sciences and Technology of Oran Mb Algeria

ISBN: (纸本)9798350349351

This paper presents the implementation of a half-bridge resonant inverter to power a dielectric barrier discharge (DBD) ozone generator. We use the PIC16F876A microcontroller-based control circuit to vary the inverter frequency. We use a step-up transformer to obtain the high voltage required for the DBD. We conducted an experimental study to investigate the impact of frequency and voltage on ozone production and power consumption. The results show that these two parameters have a strong influence. This study demonstrates the advantages of using a resonant inverter combined with optimum electrical parameter adjustment to achieve excellent energy efficiency for the DBD ozone generator. The choice of a resonant half-bridge topology aims to maximize energy efficiency, crucial in a solar-powered system. The circuit has been optimized to reduce switching losses. In addition, the development of the power source takes into account the capacitive nature of DBD reactors, using a series resonant circuit formed by the DBD capacitance and the step-up transformer inductance. The frequency range from 14 kHz to 17.5 kHz has been specifically chosen and optimized for the DBD reactor, taking into account the constraints of the PV source and the characteristics of the discharge. © 2024 IEEE.

关键词： Resonant circuits

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Soft Acoustic End-effector

Soft Acoustic End-effector

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IEEE International Conference on robotics and Automation (ICRA)

作者： Zhiyuan Zhang Michael Koch Daniel Ahmed Department of Mechanical and Process Engineering Acoustic Robotics Systems Laboratory Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Acoustic techniques have been developed as multifunctional tools for various microscale manipulations. In prevalent design paradigms, a position-fixed piezoelectric transducer (PZT) is utilized to generate ultrasound waves. However, the immobility of the PZT restricts the modulation of the acoustic field's position and orientation, consequently diminishing the adaptability and effectiveness of subsequent acoustic micromanipulation tasks. Here, we proposed a miniaturized soft acoustic end-effector and demonstrated acoustic field modulation and microparticle manipulation by adjusting PZT position and orientation. The PZT is mounted on the end of a soft robotic arm that has three individual degrees of freedom and can be deformed in 3D space by inflating or deflating each chamber. Experiments showed that the soft acoustic end-effector can change the traveling direction of microparticles and modulate the location of a standing wave field. Our approach is simple, flexible, and controllable. We envision that the soft acoustic end-effector will facilitate multiscale acoustic manipulation in interdisciplinary applications, especially, for in vivo acoustic therapies.

关键词： Three-dimensional displays Ultrasonic imaging Modulation Medical treatment Soft robotics Acoustics End effectors

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Autonomous 3D Reconstruction with Small Unmanned Aerial Vehicle (UAV) using Structure from Motion: Practical Aspects

Autonomous 3D Reconstruction with Small Unmanned Aerial Vehi...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Rayon, Nathan Stevens, Raymond Sevil, Hakki Erhan Department of Computer Science University of West Florida FL32514 United States Department of Electrical and Computer Engineering University of West Florida FL32514 United States Department of Intelligent Systems & Robotics University of West Florida FL32514 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper explores the practical considerations and challenges involved in achieving autonomous 3D reconstruction utilizing small Unmanned Aerial Vehicles (UAVs) through the framework of Structure from Motion (SFM). The utilization of small UAVs equipped with lightweight cameras presents a promising resource for cost-effective and rapid 3D mapping in various domains such as disaster response, infrastructure inspection, and search and rescue. In this study, the critical practical aspects of this process, including height level for taking images, UAV selection, number of images, image acquisition strategies, and computational time. The effectiveness and limitations of autonomous 3D reconstruction with small UAVs through practical insights are summarized, with discussions on potential advancements and areas for future research. This paper serves as a guide for researchers interested in utilizing small UAVs for autonomous 3D reconstruction tasks applications. © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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An Inductance Testing Method of Dual Three-phase Permanent Magnet Synchronous Machines Using Equivalent Electromagnetic Field Analysis

An Inductance Testing Method of Dual Three-phase Permanent M...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Zeng, Depeng Zhang, Qiang Zou, Jibin Xu, Yongxiang Pan, Hailang Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin150001 China Harbin Institute of Technology Department of Electrical Engineering Harbin150001 China

ISBN: (纸本)9798350338362

Nowadays, in the test of permanent magnet synchronous machines (PMSMs) with traditional q-axis and d-axis inductances testing methods, the machine needs to be connected to a mechanical load, and the test must be performed in the normal operating situation. However, there are some problems existing in traditional q-axis and d-axis inductances testing methods for PMSMs, such as complexity of test systems, high testing cost, etc. It restricts the testing method development of PMSMs. In this paper, a normal method for testing q-axis and d-axis inductances of dual three-phase PMSMs is proposed based on its structural characteristics and AC standstill test. The key point of the proposed method is using equivalent electromagnetic field analysis. The advantages of this method are avoiding auxiliary equipment and considering the saturation effect. In the process of testing the q-axis and d-axis inductances of dual three-phase PMSMs, AC current with DC bias is excited in a set of windings of dual three-phase PMSMs. The DC current component is used to reflect the saturation of the magnetic circuit, and the AC current component is used for the inductance test;DC current is excited the other set of winding of the machine, and it is used to adjust and fix the rotor position. Finally, the method is validated in simulation and experiment, and the error analysis of the test results is performed. © 2023 IEEE.

关键词： Inductance

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Mechanical Properties Inside Origami-Inspired Structures: An Overview

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Applied Mechanics Reviews 2025年第1期77卷 011001页

作者： Yan, Peng Huang, Hailin Meloni, Marco Li, Bing Cai, Jianguo Department of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518052 China Harbin Institute of Technology Shenzhen518052 China Key Laboratory of C & PC Structures of Ministry of Education National Prestress Engineering Research Center Southeast University Nanjing211189 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518052 China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Habin Institute of Technology Shenzhen518052 China

In recent decades, origami has transitioned from a traditional art form into a systematic field of scientific inquiry, characterized by attributes such as high foldability, lightweight frameworks, diverse deformation modes, and limited degrees-of-freedom. Despite the abundant literature on smart materials, actuation methods, design principles, and manufacturing techniques, comprehensive reviews focusing on the mechanical properties of origami-inspired structures are relatively rare and unsystematic. This review aims to fill this void by analyzing and summarizing the significant studies conducted on the mechanical properties of origami-inspired structures from 2013 to 2023. We begin with an overview that includes essential definitions of origami, classical origami patterns, and their associated tessellated or stacked structures. Following this, we delve into the principal dynamic modeling method for origami and conduct an in-depth analysis of the key mechanical properties of origami-inspired structures. These properties include tunable stiffness, bistability and multistability, metamechanical properties demonstrated by origami-based metamaterials, and bio-inspired mechanical properties. Finally, we conclude with a comprehensive summary that discusses the current challenges and future directions in the field of origami-inspired structures. Our review provides a thorough synthesis of both the mechanical properties and practical applications of origami-inspired structures, aiming to serve as a reference and stimulate further research. © 2025 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Degrees of freedom (mechanics)

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