Publications associées à Thermo-mechanical Noise Measurement of Sealed Nanobeams on a Silicon Photonics-MEMS Platform

Publications associées (21)

Project-Based Learning Approach for an Engineering Course: Challenges and Learnings of Teaching Transversal Skills

Jamie Paik, Yousef Jalali, Iris Capdevila Tristan

Project-based learning (PBL), as one of the effective teaching and learning approaches in engineering education, can create opportunities for students to address problems with real-world applications, integrate and apply knowledge, and practice and develop ...

European Society for Engineering Education (SEFI)2024

Flexible Sensor and Readout Circuitry for Continuous Ion Sensing in Sweat

Sandro Carrara, Ata Jedari Golparvar, Ali Meimandi

In this letter, we present a custom-designed and flexible readout circuitry for the characterization of flexible and planar electrolyte-gated carbon nanotube field-effect transistor-based biosensors for ammonium detection in sweat. We employed spray-deposi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Backbone curve variations on steel building seismic response

Dimitrios Lignos

A 4-story steel moment-frame building designed according to ASCE 7 was used in a numerical parameter study to assess the effects of modeling features on peak drift demands. Features studied included strength, stiffness, ductility, and degradation along wit ...

SAGE PUBLICATIONS INC2023

Walking with shorter stride length could improve knee kinetics of patients with medial knee osteoarthritis

Brigitte Jolles-Haeberli

Walking with a shorter stride length (SL) was recently proposed for gait retraining in medial knee osteoarthritis; however it was never assessed in this patient population. This study tested the hypothesis that shortening SL while maintaining walking speed ...

ELSEVIER SCI LTD2023

A Machine-Learning Architecture for Sensor Fault Detection, Isolation, and Accommodation in Digital Twins

Hossein Darvishi

Sensor technologies empower Industry 4.0 by enabling integration of in-field and real-time raw data into digital twins (DTs). However, sensors might be unreliable due to inherent issues and/or environmental conditions. This article aims at detecting anomal ...

2023

Editorial: Integration and optimization in the chemical process industry

Daniel Alexander Florez Orrego, Shivom Sharma

FRONTIERS MEDIA SA2022

Automatic Co-Design of Aerial Robots Using a Graph Grammar

Josephine Anna Eleanor Hughes

Unmanned aerial vehicles (UAVs) have broad applications including disaster response, transportation, photography, and mapping. A significant bottleneck in the development of UAVs is the limited availability of automatic tools for task-specific co-design of ...

IEEE2022

Borrowing from yourself: Faster future video segmentation with partial channel update

Evann Pierre Guy Courdier

Semantic segmentation is a well-addressed topic in the computer vision literature, but the design of fast and accurate video processing networks remains challenging. In addition, to run on embedded hardware, computer vision models often have to make compro ...

IEEE2022

Succinct Non-Interactive Arguments via Linear Interactive Proofs

Alessandro Chiesa

Succinct non-interactive arguments (SNARGs) enable verifying NP statements with lower complexity than required for classical NP verification. Traditionally, the focus has been on minimizing the length of such arguments; nowadays, researchers have focused a ...

SPRINGER2022

Explainable ensemble learning model for predicting steel section-concrete bond strength

Xianlin Wang

This study evaluates the efficiency of an explainable ensemble learning framework in precisely predicting the bond strength between steel sections with different surface treatments and various concrete types. Besides seven numerical features, two categoric ...

2022

Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region

Alfio Quarteroni, Fabio Nobile

This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. ...

2022

Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

Kamiar Aminian, Jean-Marc Vesin, Anisoara Ionescu, Mathieu Pascal Falbriard, Gaëlle Prigent

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk o ...

MDPI2021

A 1GS/s 6-to-8b 0.5mW/Qubit Cryo-CMOS SAR ADC for Quantum Computing in 40nm CMOS

Edoardo Charbon

IEEE2021

Low-Power Electro-Optic Actuators for Large-Scale Programmable Photonic Circuits

Niels Quack, Alain Yuji Takabayashi, Hamed Sattari

Photonic integrated circuits are becoming increasingly more complex, especially with the emergence of programmable photonic circuits. These require many tunable photonic elements, such as electro-optic phase shifters and tunable couplers. We will discuss o ...

IEEE2021

Adversarial Confidence Estimation Networks for Robust Stereo Matching

Seungryong Kim

Stereo matching aiming to perceive the 3-D geometry of a scene facilitates numerous computer vision tasks used in advanced driver assistance systems (ADAS). Although numerous methods have been proposed for this task by leveraging deep convolutional neural ...

IEEE Institute of Electrical and Electronics Engineers2021

Learning to See and Compute through Multimode Fibers

Demetri Psaltis, Christophe Moser, Damien Claude-Marie Loterie, Eirini Kakkava, Babak Rahmani, Ugur Tegin, Ilker Oguz, Navid Borhani, Mustafa Yildirim

We propose a computational method for controlling the output of a multimode fiber using machine learning. Arbitrary images can be projected with amplitude-only calibration (no phase measurement) and fidelities on par with conventional full-measurement meth ...

IEEE2021

Traffic Signal Prediction on Transportation Networks Using Spatio-Temporal Correlations on Graphs

Pascal Frossard, Nikolaos Geroliminis, Semin Kwak

Multivariate time series forecasting poses challenges as the variables are intertwined in time and space, like in the case of traffic signals. Defining signals on graphs relaxes such complexities by representing the evolution of signals over a space using ...

2021

Unsupervised Controllable Generation with Self-Training

Grigorios Chrysos

Recent generative adversarial networks (GANs) are able to generate impressive photo-realistic images. However, controllable generation with GANs remains an open research problem. Achieving controllable generation requires semantically interpretable and dis ...

IEEE2021

Clock Synchronization Over Networks: Identifiability of the Sawtooth Model

Pol del Aguila Pla

In this paper, we analyze the two-node joint clock synchronization and ranging problem. We focus on the case of nodes that employ time-to-digital converters to determine the range between them precisely. This specific design choice leads to a sawtooth mode ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multi-Modal Recurrent Attention Networks for Facial Expression Recognition

Seungryong Kim

Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020