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IEEE SENSORS

作者： Frederico A. Jahnert Beatriz Brusamarello Danilo F. Gomes Sérgio T. de Camargo Manoel F. da Silva Jean C. Cardozo da Silva Cicero Martelli Jucélio T. Pereira Carlos A. Bavastri Graduate Program in Mechanical Engineering Federal University of Parana (UFPR) Curitiba Brazil Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná (UTFPR) Curitiba Brazil Petrobras Research and Development Program Rio de Janeiro Brazil

Distributed Acoustic Sensors (DAS) are able to measure dynamic strain and temperature signals quantitatively along several kilometers of optical fiber using the properties of backscattering light. A drawback of DAS is the sensing resolution of around 1 meter long. This paper analyses the use of DAS as a vibration sensor for a thin plate structure using an acoustic excitation. A coiled method of arranging the sensing optical fibers enhances the measured signal and using a calibration method, the strain in the sensed region is obtained. The method can be used to characterize structures acoustically allowing the structure to detect the direction and reconstruct nearby acoustic events. Acoustic excitations were performed using a speaker at 1 meter distance to a 1 millimeter thick free-free 40 centimeters by 73 centimeter instrumented stainless steel plate inside an anechoic chamber. Results measured using reference microphones and accelerometers were compared to the optical fiber sensor through a Finite Element Model. The results demonstrate that the optical fiber system is able to measure the frequency response with an average 54 dB sound pressure level sound source chirp signal for flexural modes with a clear differentiation between angles of incidence up to 500 Hz.

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An Improved Unbiased Particle Filter

arXiv

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arXiv 2023年

作者： Jasra, Ajay Maama, Mohamed Ombao, Hernando Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process which typically leads to filtering that is subject to discretization bias. The approach in [16] establishes that when only having access to the time discretized diffusion it is possible to remove the discretization bias with an estimator of finite variance. We improve on the method in [16] by introducing a modified estimator based on the recent work of [17]. We show that this new estimator is unbiased and has finite variance. Moreover, we conjecture and verify in numerical simulations that substantial gains are obtained. That is, for a given mean square error (MSE) and a particular class of multi-dimensional diffusion, the cost to achieve the said MSE falls. Copyright © 2023, The Authors. All rights reserved.

关键词： Mean square error

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Comparative Analysis of Normal and ASD EEG Data Using Hjorth Parameters

Comparative Analysis of Normal and ASD EEG Data Using Hjorth...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Muliyadi Muliyadi Melinda Melinda Yuwaldi Away Syahrul Gazali Doctoral Program School of Engineering Post Graduate Program Universitas Syiah Kuala Banda Aceh Indonesia Electrical Engineering Department Politeknik Negeri Lhokseumawe Aceh Indonesia Dept. Electrical Engineering and Computer Engineering Faculty Universitas Syiah Kuala Banda Aceh Indonesia Dept. Neurology Universitas Syiah Kuala Banda Aceh Indonesia Mahar Mardjono National Brain Center Hospital Jakarta Indonesia

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

The increasing prevalence of autism spectrum disorder (ASD) in recent decades has underscored the need for more accurate and objective diagnostic methods. Electroencephalography (EEG) holds promise as a tool in ASD neurobiological research due to its ability to capture neural oscillatory activity with high temporal resolution. This study aims to analyze the neurophysiological differences between individuals with ASD and neurotypical populations by examining EEG data using Hjorth parameters. The preprocessing stage involved using a Butterworth filter to enhance EEG signal quality by eliminating noise in the frequency range of 4-40 Hz. The Hjorth parameters, including Activity, Mobility, and Complexity, were used to assess the statistical characteristics of the EEG signals. The analysis was conducted on EEG data collected from 5 typical individuals and 5 ASD ASD subjects. Our findings reveal that the Hjorth Activity parameter is notably lower in the ASD group across all regions, with the most significant differences observed in the left and right frontal areas, where average activity measures 0.236 μV 2 and 0.060 μV 2 in ASD individuals, compared to 0.512 μV 2 and 0.138 μV 2 in the neurotypical group. However, the Hjorth Complexity and Mobility values remained consistent between the two groups, implying that the fundamental structure of the EEG signals is relatively preserved. These findings offer insights into the neurobiological mechanisms of ASD and suggest the potential use of Hjorth parameters in developing more targeted interventions for individuals with ASD.

关键词： Human computer interaction Autism Frontal lobe Noise Neural activity Electroencephalography Complexity theory Signal resolution Robots Optimization

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Towards cross-modal causal structure and representation learning 2

Towards cross-modal causal structure and representation lear...

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2nd Machine Learning for Health Symposium, ML4H 2022

作者： Mao, Haiyi Liu, Hongfu Xiaotian Dou, Jason Benos, Panayiotis V. Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh United States Michtom School of Computer Science Brandeis University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Epidemiology University of Florida United States

Does the SARS-CoV-2 virus cause patients' chest X-Rays ground-glass opacities? Does an IDH-mutation cause differences in patients' MRI images? Conventional causal discovery algorithms, although well developed to uncover the cause-effect relationships on structured data, cannot elucidate causal relations between unstructured images and structured scalar variables due to the complexity of the former. In this paper, we consider causal discovery between images and structured (scalar) variables. Specifically, we derive low dimensional image representations to analyze with structured variables. We propose a two-module amortized variational algorithm named Cross-Modal Variational Causal representation and structure Learning (CMCL). CMCL jointly learns identifiable representations given a set of independent structured variables and causal relations via formulating latent representations and structured variables into a direct acyclic graph. Moreover, we further enforce counterfactual invariance/variance onto representations. We demonstrate that CMCL outperforms other related methods on synthetic datasets and validate causal relations on semi-synthetic datasets by visualization. © 2022 P.N. Argaw, E. Healey & I.S. Kohane.

关键词： Coronavirus

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The modified Allen test and a novel objective screening algorithm for hand collateral circulation using differential photoplethysmography for preoperative assessment: a pilot study

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Journal of Medical engineering and Technology 2020年第2期44卷 82-93页

作者： Elwali, Ahmed Moussavi, Zahra Biomedical Engineering Program University of Manitoba Winnipeg Canada Electrical and Computer Engineering Department University of Manitoba Winnipeg Canada

Hand-ischemia and artery-thrombosis are serious complications of hand artery cannulation/grafting. Screening the patency of hand arteries reduces the complications. Modified Allen Test (MAT), Barbeau's test, and Doppler/Duplex-ultrasonic test screen hand arterial patency. Each of them, however, either lacks objectivity, requires subject cooperation, or is not readily available in operating rooms. In this pilot study, we aim to provide a novel, objective, reliable, and inexpensive alternative using differential photo-plethysmography (PPG) measurement, and an artery selection algorithm. For 11 participants, MAT was executed, and PPG measurements of the thumb and little fingers were recorded for left and right hands separately. For each hand, four evaluations were conducted, then fed into the artery selection algorithm. Our proposed procedure has shown congruent results with the anatomy of blood circulation. It identified two arteries in two participants causing >50% blood reduction in the hand due to their occlusion. It also showed an elevated risk of accessing an artery in another 8 participants. Once the results of this study are confirmed in larger samples, the proposed procedure/algorithm may provide many indicators of the hand blood circulation, the effect of an artery occlusion on the hand, and a recommendation for selecting the best artery to access with the lowest possible complications. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Diseases

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Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection

arXiv

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arXiv 2024年

作者： Lee, Saehyung Mok, Jisoo Park, Sangha Shin, Yongho Jung, Dahuin Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Qualcomm Korea YH Seoul Korea Republic of School of Computer Science and Engineering Soongsil University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

In our study, we explore methods for detecting unwanted content lurking in visual datasets. We provide a theoretical analysis demonstrating that a model capable of successfully partitioning visual data can be obtained using only textual data. Based on the analysis, we propose Hassle-Free Textual Training (HFTT), a streamlined method capable of acquiring detectors for unwanted visual content, using only synthetic textual data in conjunction with pre-trained vision-language models. HFTT features an innovative objective function that significantly reduces the necessity for human involvement in data annotation. Furthermore, HFTT employs a clever textual data synthesis method, effectively emulating the integration of unknown visual data distribution into the training process at no extra cost. The unique characteristics of HFTT extend its utility beyond traditional out-of-distribution detection, making it applicable to tasks that address more abstract concepts. We complement our analyses with experiments in out-of-distribution detection and hateful image detection. Our codes are available at https://***/Saehyung-Lee/HFTT © 2024, CC BY.

关键词： Data assimilation

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Fully rubbery synaptic transistors made out of all-organic materials for elastic neurological electronic skin

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Nano Research 2022年第2期15卷 758-764页

作者： Hyunseok Shim Seonmin Jang Jae Gyu Jang Zhoulyu Rao Jong-ln Hong Kyoseung Sim Cunjiang Yu Materials Science and Engineering Program University of HoustonHoustonTX 77204 USA Department of Chemistry Seoul National UniversitySeoul 08826Republic of Korea Department of Chemistry Ulsan National Institute of Science and Technology(UNIST)Ulsan 44919Republic of Korea Department of Mechanical Engineering University of HoustonHoustonTX 77204 USA Department of Biomedical Engineering University of HoustonHoustonTX 77204USA Department of Electrical and Computer Engineering University of HoustonHoustonTX 77204 USA Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Neurologic function implemented soft organic electronic skin holds promise for wide range of applications,such as skin prosthetics,neurorobot,bioelectronics,human-robotic interaction(HRI),***,we report the development of a fully rubbery synaptic transistor which consists of all-organic materials,which shows unique synaptic characteristics existing in biological *** synaptic characteristics retained even under mechanical stretch by 30%.We further developed a neurological electronic skin in a fully rubbery format based on two mechanoreceptors(for synaptic potentiation or depression)of pressure-sensitive rubber and an all-organic synaptic *** converting tactile signals into Morse Code,potentiation and depression of excitatory postsynaptic current(EPSC)signals allow the neurological electronic skin on a human forearm to communicate with a robotic *** collective studies on the materials,devices,and their characteristics revealed the fundamental aspects and applicability of the all-organic synaptic transistor and the neurological electronic skin.

关键词： synaptic transistor stretchable electronic skin all-organic

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Evaluation of an artificial intelligence-based model in diagnosing periodontal radiographic bone loss

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Clinical Oral Investigations 2025年第4期29卷 1-8页

作者： Cassiano, Luanny de Brito Avelino da Silva, Jordão Paulino Cassiano Martins, Agnes Andrade Barbosa, Matheus Targino Rodrigues, Katryne Targino Barbosa, Ádylla Rominne Lima da Silva Gomes, Gabriela Ellen Maia, Paulo Raphael Leite de Oliveira, Patrícia Teixeira de Sousa Lopes, Maria Luiza Diniz da Silva, Ivanovitch Medeiros Dantas de Aquino Martins, Ana Rafaela Luz Department of Dentistry Federal University of Rio Grande do Norte - UFRN Rio Grande do Norte Natal Brazil Postgraduate Program in Electrical and Computer Engineering Center of Technology Rio Grande do Norte Natal Brazil Department of Dentistry Federal University of Rio Grande do Norte Av. Senador Salgado Filho 1787 Rio Grande do Norte Natal 59056-000 Brazil

Objective: To develop an artificial intelligence model based on convolutional neural network for detecting and measuring periodontal radiographic bone loss (RBL). Materials and methods: Keypoint annotations were carried out in 595 digital bitewing radiographic images using a computer Vision Annotation Tool. The dataset was splitted: 416 of these images were trained using the You Only Look Once version 8 architecture with pose estimation (YOLO-v8-pose), 119 images were destined for the validation set, and 60 images were used for the test set, resulting in a model capable of detecting keypoints related to the cementoenamel junction (CEJ) and alveolar bone crest (ABC). In order to evaluate the performance of the obtained model, the following metrics were analyzed: F1-Score, precision, sensitivity and mean average precision (mAP). Then, an algorithm was implemented to measure the RBL by calculating the Euclidean distance between CEJ and ABC. Results: The model achieved an F1-Score of 66,89%, precision of 61,1%, a sensitivity of 73,9% and an mAP of 73.8%. Conclusions: The developed model and its algorithm for identifying and measuring periodontal radiographic bone loss demonstrated promising performance, thereby presenting a potential tool for assisting in periodontal diagnosis. Further studies comparing the developed model with manual measurements performed by specialists are necessary for its validation. Clinical relevance: Applying artificial intelligence in clinical dental practice can support diagnosis, streamline clinical workflows, and inform treatment planning, representing a significant advancement in dental automation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Alveolar bone loss computer neural networks Deep learning Periodontitis Radiography

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Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi-sensor Fusion*

Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi...

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IEEE Latin American Robotics Symposium, LARS

作者： Gilmar Pereira Da Cruz Hector Azpúrua Fernando Lizarralde Gustavo Medeiros Freitas Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Minas Gerais MG Brasil Electrical Engineering Program - COPPE Universidade Federal do Rio de Janeiro RJ Brasil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is necessary to ensure better sensor fusion. Therefore, this article proposes an extrinsic sensor calibration based on markers and associated to three orthogonal planes. This technique is applied to two calibration approaches, LiDAR-Robot and LiDAR-Camera. The first one calculates the transformation between a 3D LiDAR sensor and a robot, and the second system calculates the transformation between a 3D LiDAR and an embedded RGB camera. To demonstrate the efficiency of our method, we performed simulations on the CoppeliaSim simulator and experiments in the laboratory. Then, the results show that it is possible to calibrate the sensors with the methodologies.

关键词： Visualization Laser radar Three-dimensional displays Robot vision systems Sensor fusion Cameras Sensor systems Sensors Calibration Registers

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Comparative Analysis between Three-Leg Interleaved and Conventional Bidirectional Converters Applied in Battery of Wind Power-Battery Unit Supplying an Islanded Microgrid

Comparative Analysis between Three-Leg Interleaved and Conve...

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IEEE General Meeting Power& Energy Society

作者： André C. Do Nascimento Giusep M. S. Ribeiro Lindemberg R. de Lima Pedro A. de Alcântara Luana C. S. Soares Luciano S. Barros Camila M. V. Barros Electrical Engineering Graduate Program Federal Institute of Pará Belém Brazil Electrical Engineering Graduate Program Federal University of Paraíba João Pessoa Brazil Mathematics and Computational Modeling Graduate Program Federal University of Paraíba João Pessoa Brazil Computer Systems Department Federal University of Paraíba João Pessoa Brazil

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Battery energy storage systems (BESS) are crucial for microgrids, enhancing dynamic performance and mitigating uncertainties inherent to isolated environments characterized by intermittent power generation. When microgrid is supplied by wind power in connection with BESS, the bidirectional DC-DC converter associated with BESS assumes a critical responsibility—ensuring the control of a wind power supplied DC-link. This permits the Voltage Source Inverter (VSI) to synthesize consistent voltages for the connected AC load. However, challenges emerge, particularly in arduous stress on switches of the bidirectional converter attributed to elevated current ripple. This stress does not only prejudice the overall system’s functioning but can also potentially leading it to shutdown in case of switch failure. Traditionally, the conventional buck-boost converter topology has been the go-to choice for this application, nevertheless, exploring novel converter topologies, such as interleaved bidirectional DC-DC converter (IBDC) has garnered attention, promising enhanced performance. This paper’s goal is to conduct a comparative analysis of the operation of these converters in an islanded microgrid supplied by a single Permanent Magnet Synchronous Generators (PMSG) small-scale wind turbine with a BESS system. Load variation with Maximum Power Point Tracking (MPPT) operation of the PMSG is performed during MATLAB/Simulink environment simulations. The results suggest significant advantages for the interleaved three-phase converter, such as reduced battery charging current ripple, switch disturbance, and voltage ripple in the DC-link.

关键词： Maximum power point trackers Magnetic separation Microgrids DC-DC power converters Wind power generation Permanent magnets Batteries Topology Wind turbines Stress

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