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International Solid-State Sensors, Actuators and Microsystems Conference

作者： Dorsey, K.L. Fedder, G.K. Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States Institute for Complex and Engineered Systems Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9781457701573

Electrostatic actuation is commonly used for MEMS devices such as resonators, sensors, and RF switches, but parasitic charge in the dielectric layers of the devices may cause performance issues (e.g., drift, pull-in) or decreased device lifetime. We present a precise predictive model of dielectric charging in a CMOS MEMS resonator using Frenkel-Poole conduction. The model is able to predict frequency drift within 5% of measured drift data. Use of these predictive models will lead to electrostatically actuated MEMS devices with increased stability. © 2011 IEEE.

关键词： Electrostatic actuators

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Interaction effects of temperature and stress on matched-mode gyroscope frequencies

Interaction effects of temperature and stress on matched-mod...

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2013 17th International Conference on Solid-State Sensors, Actuators and Microsystems, TRANSDUCERS and EUROSENSORS 2013

作者： Tatar, E. Guo, C. Mukherjee, T. Fedder, G.K. Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Institute for Complex Engineered Systems Carnegie Mellon University Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9781467359818

We present our initial results toward understanding the interaction of temperature and stress on resonant frequencies of a matched-mode SOI-MEMS gyroscope. We also validate a new electrostatic frequency tuning design for gyroscopes that works over large displacements. A stress and temperature gradient is formed on the gyroscope die by using on-chip silicon heaters, affecting the gyroscope frequencies. Simulation and measurements of the gyroscope frequencies under different gradient conditions are compared. We also show that the orientation of the die with respect to an asymmetric package plays an important role in frequency response of the gyroscope to environmental conditions. © 2013 IEEE.

关键词： Gyroscopes

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Bi-state control of a duffing microresonator on the falling edge of the instability

Bi-state control of a duffing microresonator on the falling ...

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2013 17th International Conference on Solid-State Sensors, Actuators and Microsystems, TRANSDUCERS and EUROSENSORS 2013

作者： Guo, Congzhong Fedder, Gary K. Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Institute for Complex Engineered Systems Carnegie Mellon University Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9781467359818

This work is the first investigation of a bi-state control technique capable of servoing on the falling edge of the microelectromechanical Duffing resonant bifurcation setpoint. The Duffing microresonator, fabricated in an SOI-MEMS process, features a sharp jump in oscillation amplitude at the bifurcation and is, therefore, ideal for ultrasensitive detection of mass or stress shifts that modify the resonance frequency and hence the jump frequency. The resonator instability tongue is characterized to identify the bifurcation points as a function of drive gain. The control system states are set through the AC drive gain while operating at a fixed drive frequency such that one of the system states is within this instability tongue whereas the second state resides outside of this tongue. The amplitude servo point is chosen at the maximum on amplitude prior to the jump event. The states are driven by 300 kHz pulse width modulation that is set much faster than the amplitude response dynamics and inhibits the system from latching off as would happen in static operation. © 2013 IEEE.

关键词： Voltage control

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Sufficient Condition for Survival of the Fittest in a Bi-virus Epidemics

Sufficient Condition for Survival of the Fittest in a Bi-vir...

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Asilomar Conference on Signals, systems and computers

作者： Augusto Santos Jose M. F. Moura Joao M. F. Xavier Dep. of Electrical and Computer Engineering Carnegie Mellon University Institute for Systems and Robotics (ISR/IST) LARSyS Instituto Superior Tecnico Universidade de Lisboa

ISBN: (纸本)9781467385770

We study the spread of two strains of virus competing for space in a network modeled by the classical logistic ordinary differential equations. In large-scale complex networks, the underlying nonlinear dynamical system is high-dimensional and performing qualitative analysis of the differential equation becomes prohibitive. The study of such systems is often deferred to numerical simulations or local analysis about equilibrium points of the system. In this paper, we extend the work developed in [1], to formally establish a simple sufficient condition for (exponentially fast) survival of the fittest in a bi-layer weighted digraph: the weaker strain dies out regardless of the initial conditions if its maximum in-flow rate of infection across nodes is smaller than the minimum in-flow rate of the stronger strain. We bound any solution of the logistic ODE by one-dimensional solutions over certain homogeneous networks, for which the system is well understood. Our global stability approach via bounds readily applies to the discrete-time logistic model counterpart.

关键词： natural selection Sufficient conditions complex networks Epidemic INITIAL CONDITIONS Differential equations Sufficient

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Two-Stream Architecture with Contrastive and Self-Supervised Attention Feature Fusion for Error-related Potentials Classification

Two-Stream Architecture with Contrastive and Self-Supervised...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Luís Garrote João Perdiz Mine Yasemin Gabriel Pires Urbano J. Nunes Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal Polytechnic Institute of Tomar Portugal

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Error-related potentials (ErrPs) extracted from electroencephalographic signals hold potential for application in Brain-Machine Interfaces, in contexts such as robot teleoperation or shared control in assistive platforms. Due to difficulties in signal classification, in part caused by its non-stationary and noisy nature, their use has not been fully realized *** work proposes a new approach to ErrP classification based on a two-stream deep learning architecture with three training stages. Its first stage is a self-supervised autoencoder architecture with a multi-head attention layer providing relevant latent features. The second stage comprises a supervised contrastive learning approach considering two backbone networks, where one inherits weights from the first stage and the other is updated by considering the feature embeddings distribution. The final stage comprises supervised classification, where the two backbones are fused and used to classify the input EEG signal. At the end of the three stages, a data-driven two-stream ErrP model is ***-five variants of the proposed approach using the Deep Convolutional Network, Shallow Convolutional Network and EEGNet backbones were tested in an ablation study and benchmarked against a large number of classical classification methods, using data from the BNCI dataset intended to assess cross subject generalization capabilities. The proposed approach obtained the best results overall, highlighting the approach’s capabilities in capturing relevant representations of the EEG signal.

关键词： Training Electric potential Deep architecture Contrastive learning Feature extraction Brain modeling Electroencephalography Noise measurement Convolutional neural networks Robots

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A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification

arXiv

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arXiv 2023年

作者： Pereira, Ricardo Barros, Tiago Garrote, Luís Lopes, Ana Nunes, Urbano J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Polytechnic Institute of Tomar Portugal

This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation-based semantic features (SSFs). These features represent, per segmentation-category, the pixel count, as well as the 2D average position and respective standard deviation values. Moreover, a two-branch network, GS2F2App, that exploits CNN-based global features extracted from RGB images and the segmentation-based features extracted from the proposed SSFs, is also proposed. GS2F2App was evaluated in two indoor scene benchmark datasets: the SUN RGB-D and the NYU Depth V2, achieving state-of-the-art results on both datasets. © 2023, CC BY.

关键词： Semantic Segmentation

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Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification

arXiv

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arXiv 2024年

作者： Pereira, Ricardo Garrote, Luís Barros, Tiago Lopes, Ana Nunes, Urbano J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Polytechnic Institute of Tomar Portugal

Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Despite the significant performance boost in classification tasks achieved in recent years, provided by the use of deep-learning-based methods, limitations such as inter-category ambiguity and intracategory variation have been holding back their performance. To overcome such issues, gathering semantic information has been shown to be a promising source of information towards a more complete and discriminative feature representation of indoor scenes. Therefore, the work described in this paper uses both semantic information, obtained from object detection, and semantic segmentation techniques. While object detection techniques provide the 2D location of objects allowing to obtain spatial distributions between objects, semantic segmentation techniques provide pixel-level information that allows to obtain, at a pixel-level, a spatial distribution and shape-related features of the segmentation categories. Hence, a novel approach that uses a semantic segmentation mask to provide Hu-momentsbased segmentation categories' shape characterization, designated by Segmentation-based Hu-Moments Features (SHMFs), is proposed. Moreover, a three-main-branch network, designated by GOS2F2App, that exploits deep-learning-based global features, object-based features, and semantic segmentation-based features is also proposed. GOS2F2App was evaluated in two indoor scene benchmark datasets: SUN RGB-D and NYU Depth V2, where, to the best of our knowledge, state-of-the-art results were achieved on both datasets, which present evidences of the effectiveness of the proposed approach. © 2024, CC BY.

关键词： Object detection

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Dynamic Environment-based Visual User Interface System for Intuitive Navigation Target Selection for Brain-actuated Wheelchairs

Dynamic Environment-based Visual User Interface System for I...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ricardo Pereira Aniana Cruz Luís Garrote Gabriel Pires Ana Lopes Urbano J. Nunes Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal Polytechnic Institute of Tomar Portugal

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

Visual user interface paradigms are one of the key modules for brain-actuated wheelchairs, which are a class of promising assistive devices that can increase the autonomy and mobility of people suffering from severe motor impairments. This work proposes a Dynamic Environment-based Visual Interface System (DEVIS) for intuitive navigation target selection for brain-actuated wheelchairs. It is composed of a novel Dynamic Visual Interface (DVI), an RGB image-based perception module (indoor scene classification, object detection and classification, and object tracking), and a P300-based BCI. The DVI displays potential navigation goals in three forms of visual cues: an RGB camera image streaming with object bounding boxes overlaid on objects detected and tracked, three global points of interest (indoor places), and two static commands. Hence, the DVI allows a user to select, through the P300-based BCI, navigation targets/commands that are flashing independently and randomly to create an oddball paradigm. Experimental evaluations were carried out in a dynamic setting with 5 participants, who were asked to select targets displayed in the DVI. The dynamic setting was obtained using RGB image sequences of the isr-RGB-D Dataset, which represents a mission performed by a mobile robotic platform. The target selection was performed through a P300-based BCI, using non-self-paced and self-paced modalities. The obtained results show that the proposed DEVIS can run in real-time and that users are able to correctly select targets with high BCI accuracy rates.

关键词： Visualization Target tracking Navigation Wheelchairs User interfaces Streaming media Real-time systems

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Globally exponentially stable attitude observer with Earth velocity estimation

Globally exponentially stable attitude observer with Earth v...

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作者： Batista, Pedro Silvestre, Carlos Oliveira, Paulo Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Department of Electrical and Computer Engineering Faculty of Science and Technology of the University of Macau China Department of Mechanical Engineering Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal

This paper presents a novel observer for attitude estimation based on a triad of high-grade rate gyros aided by a body-fixed vector measurement of a constant inertial vector, departing from the majority of solutions that consider at least two of these vectors. A cascade approach is proposed, where the first block estimates a vector that is related to the angular velocity of the Earth and a second block estimates the attitude. While the topological characteristics are relaxed in the attitude observer so that global exponential stability is achieved, an additional stage is also devised that yields estimates directly on the special orthogonal group, preserving global convergence of the estimation error. Simulation results with realistic sensor noise were performed, including extensive Monte Carlo runs. These results illustrate the convergence of the proposed solution, as well as the achievable performance and robustness to sensor noise. © 2019 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd

关键词： Angular velocity

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Collaborative diffusive source localization in wireless sensor networks

Collaborative diffusive source localization in wireless sens...

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European Signal Processing Conference (EUSIPCO)

作者： Sabina Zejnilovic João Gomes Bruno Sinopoli Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA Institute for Systems and Robotics-Instituto Superior Técnico (ISR/IST) Technical University of Lisbon Portugal

We propose a collaborative, energy efficient method for diffusive source localization in wireless sensor networks. The algorithm is based on distributed and iterative maximum-likelihood (ML) estimation, which is very sensitive to initialization. As a part of the proposed method we present an approach for obtaining a “good enough” initial value for the ML recursion based on infinite time approximation and semidefinite programming. We also present an approach for determining the sensor node that initiates the estimation process. To improve the convergence rate of the algorithm, we consider the case where selected nodes collaborate with their neighbors. Simulation results are used to characterize the performance and energy efficiency of the algorithm. We also illustrate estimation accuracy/energy consumption trade-off by varying the communication radius of sensor nodes.

关键词： Tin Maximum likelihood estimation Energy consumption Collaboration Wireless sensor networks Approximation methods

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