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Fault Prognostics of Rolling Bearings Using a Hybrid Approach ⁎

IFAC-PapersOnLine 2020年第2期53卷 4082-4087页

作者： Murilo Osorio Camargos Iury Bessa Marcos Flávio Silveira Vasconcelos D’Angelo Reinaldo Martinez Palhares Federal University of Minas Gerais - Graduate Program in Electrical Engineering Brazil Federal University of Amazonas Department of Electricity Manaus Brazil Departament of Computer Science - Universidade Estadual de Montes Claros - Av. Rui Braga s/n Vila Mauricéia 39401-089 Montes Claros MG Brasil Federal University of Minas Gerais - Department of Electronics Engineering Brazil

This paper presents a two-phase hybrid prognostics approach; in the first phase, the model’s parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. The second phase consists of using a particle filter to update the knowledge acquired so far and to predict future states of the system using in the Bayesian sense. The approach is used for an accelerated ball bearing data set, the PRONOSTIA platform, where a general fractional polynomial model is proposed as degradation model. The results of the Remaining Useful Life estimation are compared with another work in the literature, indicating its suitability and competitiveness for prognostics in this data set.

关键词： Prognostics health management remaining useful life particle filter hybrid prognostics accelerated ball bearings

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Roadmap on Nonlocality in Photonic Materials and Metamaterials

arXiv

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arXiv 2025年

作者： Monticone, Francesco Mortensen, N. Asger Fernández-Domínguez, Antonio I. Luo, Yu Tserkezis, Christos Khurgin, Jacob B. Shahbazyan, Tigran V. Chaves, André J. Peres, Nuno M.R. Wegner, Gino Busch, Kurt Hu, Huatian della Sala, Fabio Zhang, Pu Ciracì, Cristian Aizpurua, Javier Babaze, Antton Borisov, Andrei G. Chen, Xue-Wen Christensen, Thomas Yan, Wei Yang, Yi Hohenester, Ulrich Huber, Lorenz Wubs, Martijn de Liberato, Simone Gonçalves, P.A.D. de Abajo, F. Javier García Hess, Ortwin Tarasenko, Illya Cox, Joel D. Jelver, Line Dias, Eduardo J.C. Sánchez, Miguel Sánchez Margetis, Dionisios Gómez-Santos, Guillermo Stauber, Tobias Tretyakov, Sergei Simovski, Constantin Pakniyat, Samaneh Gómez-Díaz, J. Sebastián Bondarev, Igor V. Biehs, Svend-Age Boltasseva, Alexandra Shalaev, Vladimir M. Krasavin, Alexey V. Zayats, Anatoly V. Alù, Andrea Song, Jung-Hwan Brongersma, Mark L. Levy, Uriel Long, Olivia Y. Guo, Cheng Fan, Shanhui Bozhevolnyi, Sergey I. Overvig, Adam Prudêncio, Filipa R. Silveirinha, Mário G. Gangaraj, S. Ali Hassani Argyropoulos, Christos Huidobro, Paloma A. Galiffi, Emanuele Yang, Fan Pendry, John B. Miller, David A.B. School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States POLIMA Center for Polariton-driven Light–Matter Interactions University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark D-IAS—Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark Departamento de Física Teórica de la Materia Condensada Universidad Autónoma de Madrid MadridE-28049 Spain Universidad Autónoma de Madrid MadridE-28049 Spain School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Physics Jackson State University JacksonMS39217 United States Department of Physics Aeronautics Institute of Technology SP So Jos dos Campos12228-900 Brazil Departamento de Física Universidade do Minho BragaP-4710-057 Portugal Av Mestre José Veiga Braga4715-330 Portugal Max-Born-Institut Berlin12489 Germany Humboldt-Universität zu Berlin Institut für Physik AG Theoretische Optik and Photonik Berlin12489 Germany Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Via Barsanti 14 Arnesano73010 Italy Via Monteroni Campus Unisalento Lecce73100 Italy School of physics Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Donostia International Physics Center DIPC Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Electricity and Electronics University of the Basque Country Leioa48940 Spain Department of Applied Physics University of the Basque Country Donostia20018 Spain Université Paris-Saclay CNRS Institut des Scienc

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally made in optical material modeling. On one end, the growing interest in plasmonic, polaritonic and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces–can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In the case of metasurfaces, in particular, nonlocality engineering has become a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward–toward new scientific discoveries and technological advancements. Copyright © 2025, The Authors. All rights reserved.

关键词： Nanocrystals

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Contributors to the Lab on a Chip cell and tissue engineering in microsystems special issue

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Lab on a Chip 2007年第6期7卷 667-671页

作者： Bhatia, Sangeeta N. Chen, Christoper Bashir, Rashid Beebe, David J. Desai, Tejal Gottwald, Eric Khademhosseini, Ali Langer, Robert S. Piel, Matthieu Takayama, Shuichi Thorsen, Todd Tien, Joe Voldman, Joel Vunjak-Novakovic, Gordana Wu, Mingming Yu, Hanry Massachusetts Institute of Technology Harvard-MIT Division of Health Sciences and Technology Department of Electrical Engineering and Computer Science United States Laboratory for Multiscale Regenerative Technologies United States Department of Innovation University of Pennsylvania Department of Bioengineering United States Cell Biology and Physiology Program Cell Growth and Cancer Program Tissue Microfabrication Laboratory Department of Electrical and Computer Engineering and Biomedical Engineering Purdue University United States Department of Electronics University of Glasgow United Kingdom Department of Physiology and Bioengineering University of California San Francisco CA United States California Institute for Quantitative Biomedical Research UCSF/UC Berkeley Graduate Group in Bioengineering United States Laboratory of Therapeutic Micro and Nanotechnology Institute for Biological Interfaces Germany 3D-Cell Culture Techniques Group Institute for Biological Interfaces Germany Department of Medicine and Health Sciences and Technology Massachusetts Institute of Technology (MIT) United States Institut Curie UMR 144 IC/CNRS France Biomedical Engineering Department University of Michigan United States Department of Biomedical Engineering Macromolecular Science and Engineering Program United States Sibley School of Mechanical and Aerospace Engineering School of Chemical and Molecular Engineering Cornell University United States National University of Singapore Singapore Institute of Bioengineering and Nanotechnology A STAR Singapore

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Guaranteed methods based on constrained zonotopes for set-valued state estimation of nonlinear discrete-time systems

arXiv

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arXiv 2019年

作者： Rego, Brenner S. Raffo, Guilherme V. Scott, Joseph K. Raimondo, Davide M. Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte MG 31270-901 Brazil Department of Electronics Engineering Federal University of Minas Gerais Belo Horizonte MG 31270-901 Brazil Department of Chemical and Biomolecular Engineering Clemson University ClemsonSC United States Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

This paper presents new methods for set-valued state estimation of nonlinear discrete-time systems with unknown-but-bounded uncertainties. A single time step involves propagating an enclosure of the system states through the nonlinear dynamics (prediction), and then enclosing the intersection of this set with a bounded-error measurement (update). When these enclosures are represented by simple sets such as intervals, ellipsoids, parallelotopes, and zonotopes, certain set operations can be very conservative. Yet, using general convex polytopes is much more computationally demanding. To address this, this paper presents two new methods, a mean value extension and a first-order Taylor extension, for efficiently propagating constrained zonotopes through nonlinear mappings. These extend existing methods for zonotopes in a consistent way. Examples show that these extensions yield tighter prediction enclosures than zonotopic estimation methods, while largely retaining the computational benefits of zonotopes. Moreover, they enable tighter update enclosures because constrained zonotopes can represent intersections much more accurately than zonotopes. Copyright © 2019, The Authors. All rights reserved.

关键词： Enclosures

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Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices Induced by Random Interface Traps

Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices ...

引用

IEEE Conference on Nanotechnology

作者： Sekhar Reddy Kola Min-Hui Chuang Yiming Li Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering Institute of Communications Engineering Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan

Three-dimensional (3D) bulk fin-typed field effect transistors (FinFETs) have emerged as key devices that can scale down the technology node beyond 22-nm. However, the scaled devices have created new sources of fluctuation inherent in 3D geometry. The interface trap is one such fluctuation that is caused by the trapping and de-trapping of charge carriers and has an adverse effect on device characteristics and variability. In this work, we study impacts of random interface traps (RITs) on electrical characteristic of bulk FinFETs by using a 3D quantum-mechanically corrected device simulation. RIT position effects on short channel effects (SCEs) are examined with physical governed influence to show the major fluctuations. More than 50% reductions of the RITs-induced characteristic fluctuation of the germanium (Ge) devices are observed, compared with Si devices. The Ge ones can reduce SCE variations and exhibit high immunity to RITs.

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

Predicting Microsatellite Instability from Histology Images ...

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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A Comparative Study of DeepLabCut and Other Open-Source Pupillometry Data Analysis Algorithms – Which to Choose?

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Machine Graphics and Vision 2024年第2期33卷 77-90页

作者： Badkul, Amitesh Mishra, Sonakshi Kommajosyula, Srinivasa P. Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Department of Pharmacy Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Ph.D. Program in Computer Science The Graduate Center The City University of New York New YorkNY United States

Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study aims to compare the accuracy of computer vision-based algorithms (Swirski, Starburst, PuRe, ElSe, ExCuSe algorithms) and the machine learning algorithm, DeepLabCut, to the double-blinded human examiners (gold-standard). Training of DeepLabCut with different architectures and a variable number of markers (2-9 markers) was done on an open-source dataset. The duration of training was statistically longer for the ResNet152 model compared to the MobileNet model. The pupil diameters in computer vision-based software such as PuRe, Starburst, and Swirski were statistically different from human measurements. MobileNet 2 and 3 marker models were the closest to the human measurements. In conclusion, this work highlights the efficiency of lower marker models based on MobileNet architecture in DeepLabCut, which consumes fewer computational resources and is more accurate. © 2024 Institute of Information Technology, Warsaw University of Life Sciences - SGGW. All rights reserved.

关键词： Adversarial machine learning

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Identification of D- and L-Phenylalanine Enantiomeric Mixtures by Employing Deep Neural Network Models

SSRN

引用

SSRN 2023年

作者： Nigdelioglu, Ebru Toprak, Elif Guney Akkurt, Melike Erol Barkana, Duygun Kazanci, Murat Uyaver, Sahin Calik, Nurullah Istanbul Medeniyet University Nanoscience and Nanoengineering Program Graduate School Istanbul Medeniyet University Istanbul34700 Turkey Istanbul Medeniyet University School of Engineering and Natural Sciences Department of Biomedical Engineering Istanbul Turkey Istanbul34700 Turkey Yeditepe University Faculty of Engineering Department of Electrical and Electronics Engineering Kayışdagı Istanbul34755 Turkey Marmara University Faculty of Technology Department of Computer Engineering Maltepe Istanbul34854 Turkey

Phenylalanine is an aromatic essential amino acid that exhibits the tendency to self-aggregate into fibrillar structures in its enantiomerically pure form. This observation was indicated as the underlying mechanism of phenylketonuria, which is a genetic condition associated with various neurological, physical, and developmental issues, characterized with phenylalanine buildup in the brain. The presence of D-phenylalanine was demonstrated previously to inhibit the formation of fibrils by L-phenlyalanine, indicating its potential use in phenylketonuria treatment. In this study, several combinations of D and L-phenylalanine were examined with the help of state-of-the-art deep learning methods for their fibril forming capacity, demonstrating the usefulness and accuracy of deep learning methods in distinguishing between different self-assembled structures. © 2023, The Authors. All rights reserved.

关键词： Self assembly

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Asynchronous Multi-Task Learning Based on One Stage YOLOR Algorithm

Asynchronous Multi-Task Learning Based on One Stage YOLOR Al...

引用

IEEE International Symposium on Industrial electronics (ISIE)

作者： Cheng-Fu Liou Tsung-Han Lee Jiun-In Guo Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Pervasive Artificial Intelligence Research Labs (PAIR Labs) Wistron-NCTU Embedded Artificial Intelligence Research Center Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan

The You Only Learn One Representation (YOLOR) approach is an object detector that can encode implicit knowledge and explicit knowledge of multiple tasks simultaneously. However, the requirement of jointly feeding data is not a friendly setting for an edge device due to the high computational cost. A better strategy is to learn the concept of the new task on the device individually, one by one, without access to the old data. In other words, the model has to deal with multiple tasks asynchronously. In this work, we extend the multi-purpose network YOLOR to asynchronous multi-task learning to learn domain invariant features, which focus on capturing the relatedness between the weight of the previous task and data of the subsequent task. Further, as the number of tasks gradually increases, we accumulate significant weights by introducing task-specific masks and expert modules; the former can automatically identify important filters to prevent modification caused by new tasks, and the latter address the kernel space misalignment problem to perform multi-task feature selection. We experimentally demonstrate that the proposed training strategy significantly outperforms the traditional solution in learning multiple tasks at different times on a public dataset, which supports that the proposed approach is more competitive for resource-limited edge devices.

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A Security Testbed for Networked DES Control Systems

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IFAC-PapersOnLine 2022年第28期55卷 128-134页

作者： Michel R.C. Alves Karen Rudie Patrícia N. Pena Graduate Program in Electrical Engineering - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil Department of Electrical and Computer Engineering and Ingenuity Labs Research Institute Queen's university Kingston Ontario K7L 3N6 Canada Department of Electronics Engineering - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil

In this paper we present an implementation scheme for a networked control system where the coordination between devices is done by supervisory control theory. The system is intended to be used as a testbed for DES security-related techniques. We provide some examples of attacks whose effect can be evaluated using the proposed setup. The hardware and software are based on low-cost devices and can be modified to suit different control systems. The details of the implementation are available on a free online repository.

关键词： Discrete-Event Systems Supervisory control Deception attacks Networked Control

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