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

作者： Ballesteros, Erik Carpenter, Kalind Asada, H. Harry Department of Mechanical Engineering Massachusetts Institute of Technology Course 2 CambridgeMA02139 United States Advanced Robotics Systems Group 347Z NASA Jet Propulsion Laboratory PasadenaCA91011 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This paper investigates the effectiveness of a type of wearable robot, known as Supernumerary Robotic Limbs (SuperLimbs) in assisting an astronaut performing partial-gravity ExtraVehicular Activities (EVAs). SuperLimbs can directly address a key technology gap identified by NASA concerning that of incapacitated crew rescue devices during partial-gravity EVAs. To contextualize SuperLimbs in human spaceflight application, we start by reviewing other forms of wearable robotics technologies and perform a qualitative comparison with SuperLimbs. From there, we present a suite of operational modes that SuperLimbs is capable of delivering in a suited partial-gravity EVA. Within the operational mode suite, we selected the most urgent use-case: that of performing a post-fall recovery, and reviewed the results from a pilot-human study. To validate the effectiveness of SuperLimbs in providing the necessary assistive forces needed for a post-fall recovery, a series of validation experiments was performed with a prototype SuperLimbs system. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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An Empirical Comparison of Machine and Deep Learning Algorithms for Predicting Maternal Health Risk 5th

An Empirical Comparison of Machine and Deep Learning Algorit...

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5th EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2024

作者： N, Srinivasa Gupta Valarmathi, B. Kavitha, A. Gopini, Sai Bhuvan Seela, Hari Kumar Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced of Sciences Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9783031770777

Maternal health is among the greatest challenges in the world, especially in rural areas as there lack medical practitioners, they do not have easily accessible publics clinics and transport is difficult. Therefore, high rates of maternal as well as infant morbidity and mortalities are recorded. This research utilizes Artificial Intelligence (AI) with machine learning algorithms to forecast and address maternal health hazards right at their onset stage. The current research utilizes the concept of AI along with many Machine Learning (ML) methods like the Ensemble Learning Model (ELM), Random Forest (RF), K-Nearest Neighbour (KNN), Decision-Tree (DT), XG-Boost (XGB), Cat Boost (CB), and Gradient Boosting (GB), along with Synthetic Minority Over-sampling Technique (SMOTE) algorithm used for dealing with the problem class imbalance within the data set. SMOTE algorithm is utilized for the dataset balancing process. The handling system involves refining data preprocessing with the help of feature engineering and robust data cleaning which makes sure that anomalies do not erode the reliability of the predictive model. The existing methods [1] used RF (90%), DT (87%), XGB (85%), CB (86%), and GB (81%) algorithms and were compared with the accuracies of the proposed models like Logistic Regression (LR), Ensemble Learning Bagging (ELB), Ensemble Learning Stacking (ELS), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The existing methods used only imbalance dataset. The accuracies of the proposed models with using SMOTE algorithm (balanced dataset) are LR (61.33%), KNN (81%), ELB (92.33%), ELS (90.66%) CNN (40.67%), RNN (59.67%), LSTM (54%), GRU (56%) respectively. Among these methods, ELB achieved 92.33% of accuracy with using SMOTE algorithm using imbalanced dataset. Whereas the accuracies of the proposed models without using SMOTE algorithm (imbalanced dataset) are LR (66.09%), KNN (68.47%)

关键词： Convolutional neural networks

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Feasibility Analysis of Carbide Broaching Tools in the Machining of Inconel 718 19th

Feasibility Analysis of Carbide Broaching Tools in the Machi...

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19th Global Conference on Sustainable Manufacturing, GCSM 2023

作者： Sastoque-Pinilla, Leonardo del Olmo, Ander Tapia, Endika López-Novoa, Unai de Lacalle, Luis Norberto López Advanced Manufacturing Centre for Aeronautics University of the Basque Country Zamudio Biscay48170 Spain Department of Computer Languages and Systems University of the Basque Country Biscay Bilbao48013 Spain Department of Mechanical Engineering University of the Basque Country Biscay Bilbao48013 Spain

ISBN: (纸本)9783031774287

Broaching is a highly efficient process for producing high-quality parts with precise dimensions. However, process efficiency alone does not guarantee sustainability. To address this, several key factors need to be considered, including process parameters, machine configuration, material and design of the workpiece, and tool characteristics. Several studies have focused on investigating the sustainability of the broaching process and its environmental impact, but the broaching tool has been less studied, even though it determines the geometric and sur-face quality of the broached grooves. To address this gap in the literature, this study compares the performance of three carbide tools for broaching Inconel 718 under identical machining conditions. The aim is to evaluate the selection of tools that align with the machine and workpiece material conditions to maintain a highly efficient process while improving process sustainability. © The Author(s) 2025.

关键词： Carbide cutting tools

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Lag Synchronization and Lag H∞ Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks Suffering Topology Attacks

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IEEE Transactions on Control of Network systems 2025年

作者： Wang, Jin-Liang Zhao, Xin-Yu Ren, Shun-Yan Huang, Tingwen Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Tiangong University School of Electronics & Information Engineering Tianjin300387 China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one hand, by adopting state feedback control scheme, the problem of the lag synchronization for the multistate coupled CRNN is addressed. Moreover, the influences of external disturbances for the lag synchronization of the CRNN with multistate couplings are also taken into consideration. On the other hand, several lag and lag H∞ synchronization conditions for CRNN with multiple spatial-diffusion couplings are derived under the help of the Kronecker product and the state feedback control method. Finally, two numerical examples are provided to verify the correctness of the derived criteria. © 2014 IEEE.

关键词： State feedback

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MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion

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IEEE Transactions on Multimedia 2025年

作者： Lei, Jia Li, Jiawei Liu, Jinyuan Wang, Bin Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1010 New Zealand Ulster University Intelligent Systems Research Center LondonderryBT52 1SA United Kingdom

Multi-modality image fusion (MMIF) entails synthesizing images with detailed textures and prominent objects. Existing methods tend to use general feature extraction to handle different fusion tasks. However, these methods have difficulty breaking fusion barriers across various modalities owing to the lack of targeted learning routes. In this work, we propose a multi-scenario feature joint learning architecture, MLFuse, that employs the commonalities of multi-modality images to deconstruct the fusion progress. Specifically, we construct a cross-modal knowledge reinforcing network that adopts a multipath calibration strategy to promote information communication between different images. In addition, two professional networks are developed to maintain the salient and textural information of fusion results. The spatial-spectral domain optimizing network can learn the vital relationship of the source image context with the help of spatial attention and spectral attention. The edge-guided learning network utilizes the convolution operations of various receptive fields to capture image texture information. The desired fusion results are obtained by aggregating the outputs from the three networks. Extensive experiments demonstrate the superiority of MLFuse for infrared-visible image fusion and medical image fusion. The excellent results of downstream tasks (i.e., object detection and semantic segmentation) further verify the high-quality fusion performance of our method. The code is publicly available at https://***/jialei-sc/MLFuse. © 1999-2012 IEEE.

关键词： Semantic Segmentation

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Comparison of the time-dependent discriminatory accuracy of femoral strength and bone mineral density for predicting future hip and major osteoporotic fractures: a 16-year follow-up of the AGES-Reykjavik cohort

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Osteoporosis International 2025年 1-10页

作者： Praveen, Anitha D. Jha, Dheeraj Baker, Alexander Fleps, Ingmar Björnsson, Páll Ellingsen, Lotta María Aspelund, Thor Sigurdsson, Sigurdur Gudnason, Vilmundur Pálsson, Halldór Matchar, David Johannesdottir, Fjola Ferguson, Stephen J. Helgason, Benedikt Future Health Technologies Programme Singapore-ETH Centre CREATE campus 1 Create Way CREATE Tower #06-01 138602 Singapore Singapore Institute for Biomechanics ETH Zürich Zurich Switzerland College of Mechanical Engineering Boston University Boston MA United States Faculty of Electrical and Computer Engineering University of Iceland Reykjavik Iceland Centre of Public Health Sciences Faculty of Medicine University of Iceland Reykjavik Iceland The Icelandic Heart Association Research Institute Kopavogur Iceland Faculty of Industrial Engineering Mechanical Engineering and Computer Science School of Engineering and Natural Sciences University of Iceland Reykjavik Iceland Department of Medicine Duke University Durham NC United States Programme in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Center for Advanced Orthopaedic Studies Beth Israel Deaconess Medical Center and Department of Orthopaedic Surgery Harvard Medical School Boston MA United States

Summary: The discriminative accuracy of femoral strength was significantly higher than that of aBMD over 16 years of follow-up for classifying hip fractures and major osteoporotic fractures. The use of accurate thresholds, whether for aBMD or other imaging-based biomarkers, is crucial to improve sensitivity and identify high-risk older adults. Background: Areal bone mineral density (aBMD) is a surrogate for bone strength but has limited prognostic value. Finite element (FE)–derived femoral strength offers a biomechanical alternative to aBMD for fracture risk assessment, but its long-term predictive value remains unclear. This study compared the discriminatory accuracy of aBMD and femoral strength for hip (HFs) and major osteoporotic fractures (MOFs) over 16 years, accounting for mortality risk. Methods: In the prospective Age Gene/Environment Susceptibility‐Reykjavik (AGES‐Reykjavik) Study, elderly participants underwent CT scans at entry and automated algorithms were used to compute aBMD and femoral strength. Time-dependent area under the receiver operating characteristic curves (AUC) was used to compare the predictive abilities of aBMD and femoral strength. Optimal cutoffs at the Youden’s index were compared with the World Health Organization (WHO)–defined aBMD cutoffs at various time points. Results: The cohort comprised 4621 older adults (mean age 76 ± 5 years). Femoral strength had a significantly higher AUC than aBMD in identifying HFs (p < 0.05) from the 6th year in males and females, while their AUCs in predicting MOFs were similar. WHO-defined aBMD showed low sensitivity (17–52%) but high specificity (78–94%) for both HFs and MOFs. The sensitivity of optimal femoral strength was significantly higher than that of aBMD at comparable specificity by 5–19% for HFs and 2–10% for MOFs (p < 0.05). Conclusions: Both image-based markers predict long-term fracture risk and enable opportunistic screening with existing CT scans. However, femoral strength demonstrates be

关键词： Bone mineral density Competing risk Diagnostic accuracy Finite-element modelling Osteoporotic fractures Prediction Time-dependent AUC

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Cutting Skill Assessment by Motion Analysis Using Deep Learning and Spatial Marker Tracking

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IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Su, Bai-Quan Ma, Xu-Dong Li, Weihan Kuang, Zi-Ao Gong, Yi Wang, Gang Zhang, Qingqian Liu, Wenyong Li, Changsheng Gao, Li Wang, Junchen Beijing University of Posts and Telecommunications Medical Robotics Laboratory School of Automation Beijing100876 China University of Tokyo School of Mechanical Engineering Tokyo113-0033 Japan Beijing University of Posts and Telecommunications School of Computer Science Beijing100876 China Peking University General Surgery Department Beijing100191 China Beihang University Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beijing100083 China Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China Peking University Department of Periodontology National Stomatological Center School and Hospital of Stomatology National Clinical Research Center for Oral Diseases National Engineering Research Center of Oral Biomaterials and Digital Medical Devices Beijing100081 China Beihang University School of Mechanical Engineering and Automation Beijing100083 China

The assessment of surgical skill is crucial for indicating a surgeon's proficiency. While motion analysis of surgical tools is widely used in endoscopic surgery, it is not commonly applied to open surgery. Instead, open surgery skill assessment relies on observing the trajectory of surgical tools on tissue. This observation-based method often lacks clear standards, leading to inaccurate assessments. This paper presents a method for evaluating cutting skill in open surgery through scalpel motion analysis. A 3D multiple-facet ArUco code cube is designed, and a dataset of tip coordinate system poses for various scalpels in the ArUco code coordinate system (ACS) is established using the pivot calibration method. The YOLOv8 model and an image dataset of different scalpels are used to identify the scalpel type and select its tip position. The tip position is then transformed from ACS to a binocular camera coordinate system (BCS), representing the incision curve made by the scalpel. Five assessment metrics are proposed to quantify the surgeon's cutting skill: average incision curvature deviation, incision length difference, incision endpoint deviation, average incision deviation, and average cutting jerk. Experiments involving twenty expert and novice surgeons performing four common incisions (straight line, polyline, semicircle, and cross line) demonstrate the metrics' effectiveness. The metrics provide a clear, objective display of individual cutting skills, and a combined ranking reveals comparative skill levels. This study offers a precise method for evaluating surgeons' cutting skills with a scalpel in open surgery. © 1964-2012 IEEE.

关键词： Surgery

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Progression to cell death correlates with neurite swelling induced by stretch injury

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Journal of Biomechanical Science and engineering 2012年第SPECIALISSUE.4期7卷 406-415页

作者： Nakadate, Hiromichi Umahashi, Hiroto Kakuta, Akira Aomura, Shigeru Graduate School of System Design Tokyo Metropolitan University 6-6 Asahigaoka Hino Tokyo 191-0065 Japan Advanced Course of Mechanical and Computer Systems Engineering Tokyo National College of Technology Japan

Diffuse axonal injury (DAI), a major component of traumatic brain injury, is associated with rapid deformation of brain tissue resulting in the stretching of neural axons. Focal axonal swelling, which is the morphological hallmarks of DAI pathology, leads to the disconnection of neurons from tissues, resulting in cell death. Our goal is better understanding of neuronal tolerance and help to predicting the pathogenesis of DAI from mechanical loading to the head. In present study, we developed an in vitro stretch injury device that subjected cultured cells to a wide range of mechanical stretch that are experienced during in vivo head injury. Then using this device, PC12 cells, which extend structurally axon-like cylindrical protrusions in culture, were stretched to a strain of 0.15, 0.30, or 1.00 at strain rates of 30, 40, or 80 s-1, or left as static culture. Following mechanical loading, we assessed neurite swelling resulting in neuronal detachment from culture substrate and neuronal death. As a result, the increase in early neurite swelling was dependent on the severity of the stretch, and neuronal adhesion and viability at 24 h post-injury decrease in a stretch-dependent manner. These results suggest that the formation of neurite swellings correlates with the progression to neuronal death. © 2012 by JSME.

关键词： Strain rate

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Effects of the lift valve opening area on water hammer pump performance and flow behavior in the valve chamber

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International Journal of Fluid Machinery and systems 2012年第3期5卷 109-116页

作者： Saito, Sumio Dejima, Keita Takahashi, Masaaki Hijikata, Gaku Iwamura, Takuya Department of Mechanical Engineering Tokyo National College of Technology 1220-2 Kunugida-machi Hachioji-shi Tokyo 193-0997 Japan Environmental Systems Engineering Course Nagaoka University of Technology 1603-1 Kamitomioka-machi Nagaoka-shi Niigata 940-2188 Japan Mechanical and Computer Systems Engineering Advanced Engineering Course Tokyo National College of Technology 1220-2 Kunugida-machi Hachioji-shi Tokyo 193-0997 Japan

Water hammer pumps can effectively use the water hammer phenomenon for water pumping. They are capable of providing an effective fluid transport method in regions without a well-developed social infrastructure. The results of experiments examining the effect of the geometric form of water hammer pumps by considering their major dimensions have been reported. However, these conventional studies have not fully evaluated pump performance in terms of pump head and flow rate, common measures of pump performance. The authors have focused on the effects on the pump performance of various geometric form factors in water hammer pumps. The previous study examined how the hydrodynamic characteristics was affected by the inner diameter ratio of the drive and lift pipes and the angle of the drive pipe, basic form factors of water hammer pumps. The previous papers also showed that the behavior of water hammer pump operation could be divided into four characteristic phases. The behavior of temporal changes in valve chamber and air chamber pressures according to the air volume in the air chamber located downstream of the lift valve was also clarified in connection with changes in water hammer pump performance. In addition, the effects on water hammer pump performance of the length of the spring attached to the drain valve and the drain pipe angle, form factors around the drain valve, were examined experimentally. This study focuses on the form of the lift valve, a major component of water hammer pumps, and examines the effects of the size of the lift valve opening area on water hammer pump performance. It also clarifies the behavior of flow in the valve chamber during water hammer pump operation.

关键词： Transport properties

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Uniaxial stretch-induced axonal injury thresholds for axonal dysfunction and disruption and strain rate effects on thresholds for mouse neuronal stem cells

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Journal of Biomechanical Science and engineering 2017年第1期12卷 16-00598页

作者： Kurtoglu, Evrim Nakadate, Hiromichi Kikuta, Kazuhiro Aomura, Shigeru Kakuta, Akira Graduate School of System Design Tokyo Metropolitan University Tokyo Japan Advanced Course of Mechanical and Computer Systems Engineering Tokyo National College of Technology 1220-2 Kunugida-machi Hachioji-shi Tokyo193-0997 Japan

In this paper, the proposed study aims to achieve a better understanding of neuronal tolerance and contribute to the prediction of the secondary degeneration of diffuse axonal injury (DAI). Therefore, a uniaxial stretching device which subjected cultured neurons to uniaxial stretch was employed to evaluate the effect of strain and strain rate along axon to realize the injury threshold. Neurons differentiated from mouse neuronal stem cells were injured and the morphology was observed before and after stretching with strains of 0.10, 0.12, 0.18, 0.23 at strain rates of 8, 11, 19, 26 s-1 respectively. Results suggest that the threshold for axonal dysfunction is around 0.18 strain whereas the threshold for axonal disruption is around 0.23 and the results of strain rate effect investigations on axonal dysfunction and disruption around these threshold values indicated that higher strain rate values such as 50 s-1 may have diminishing effects on threshold for axonal disruption. © 2017 The Japan Society of mechanical Engineers.

关键词： Stem cells

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