Decentralized clustering for node-variant graph filtering with graph diffusion LMS

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This work presents the study of suspended Y-cut Lithium Niobate shear bulk acoustic resonators for wide band filter applications in the frequency range of 3.5-4.5GHz. The resonators consist of a Lithium Niobate film with Aluminum top interdigitated electro ...

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

This work deals with a control strategy to regulate homogeneous reaction systems in reactors equipped with a cooling jacket. The reaction system is expressed in terms of vessel extents and viewed as a single-input (the inlet coolant temperature), two-outpu ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

Over the past two decades, the thermo-hydro-mechanical behavior of earth-contact structures such as piles, walls, slabs, and tunnels, which simultaneously provide structural support and energy supply, has been studied through various field experiments and ...

Sexual harassment is prevalent at all levels of higher education and research and in all disciplines, which means that engineering education is no exception. Following the #MeToo movement, students have started to report cases of abuses publicly in our ins ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...

A programmable patient-customized epileptic seizure detector is proposed in this paper to enable neurologists and patients to have constructive interactions with the implantable medical device. The programmability feature is enabled by designing a low-powe ...

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

Current procedures for the rapid inspection of buildings and infrastructure are subjective, time-consuming, and cumbersome to document, necessitating new technologies to automate the process and eliminate these shortcomings. Fortunately, recent development ...

Electrofacies using well logs play a vital role in reservoir characterization. Often, they are sorted into clusters according to the self-similarity of input logs and do not capture the known underlying physical process. In this paper, we propose an unsupe ...

Stable and uniform beams with low divergence are required in particle accelerators; therefore, beyond the accelerated current, measuring the beam current spatial uniformity and stability over time is necessary to assess the beam performance, since these pa ...

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types ...

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Nickel iron layered double hydroxide (NiFe LDH) is one of the best oxygen evolution reaction (OER) catalysts in alkaline electrolytes. However, it performs poorly in neutral electrolytes, and the detailed mechanism is still unclear. Herein, we introduce el ...

Decentralized clustering for node-variant graph filtering with graph diffusion LMS

Chattez avec Graph Search

Toward Band n78 Shear Bulk Acoustic Resonators Using Crystalline Y-Cut Lithium Niobate Films With Spurious Suppression

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Thermo-hydro-mechanical behavior of energy barrettes: Field experiments and numerical simulations

Supporting Well-Being: A Digital Intervention Model for Disclosing Sexual Harassment in Higher Education

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Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Investigation of nickel iron layered double hydroxide for water oxidation in different pH electrolytes