Optimal Design of the Propulsion System of a Hyperloop Capsule

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A user’s benefit from the energy stored in a battery over its lifetime depends on the time-varying characteristics of the battery, which are in turn affected by the chosen usage behavior. Both the capacity shrinkage and the number of lifetime cycles are st ...

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized S ...

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good g ...

Orthogonal group synchronization is the problem of estimating n elements Z(1),& mldr;,Z(n) from the rxr orthogonal group given some relative measurements R-ij approximate to Z(i)Z(j)(-1). The least-squares formulation is nonconvex. To avoid its local minim ...

In an era where portable electronic devices are indispensable for a wide range of activities, the need for displays that provide both long-lasting battery life and excellent visibility in different lighting conditions is increasingly important. Emissive di ...

This paper develops a fast algorithm for computing the equilibrium assignment with the perturbed utility route choice (PURC) model. Without compromise, this allows the significant advantages of the PURC model to be used in large-scale applications. We form ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

The European Union's Green Deal aims for a 55% reduction in greenhouse gas emissions by 2030. To reach this goal, a massive integration of Renewable Energy Sources (RES) into the power grid is necessary. As RES become a large part of the electricity genera ...

The aqueous zinc-ion battery is promising as grid scale energy storage device, but hindered by the instable electrode/electrolyte interface. Herein, we report the lean-water ionic liquid electrolyte for aqueous zinc metal batteries. The lean-water ionic li ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Dielectric Elastomer Actuators (DEAs) are a type of smart material described as compliant capacitors. They show impressive performances as soft actuators, such as a high strain and fast response. Nonetheless, replicating natural muscle function with DEAs h ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

The thesis explores the issue of fairness in the real-time (RT) control of battery energy storage systems (BESSs) hosted in active distribution networks (ADNs) in the presence of uncertainties by proposing and experimentally validating appropriate control ...

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

The terminology of neurological disorders encompasses a range of serious illnesses (e.g., epilepsy, Alzheimer's disease) leading to morbidity, disability, and stigma. Epilepsy alone affects over 50 million people worldwide, and these figures are rising as ...

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

Optimal Design of the Propulsion System of a Hyperloop Capsule

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Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

The effect of smooth parametrizations on nonconvex optimization landscapes

BENIGN LANDSCAPES OF LOW-DIMENSIONAL RELAXATIONS FOR ORTHOGONAL SYNCHRONIZATION ON GENERAL GRAPHS

MEMS-based Tunable Metasurface for Reflective Display Applications

Perturbed Utility Stochastic Traffic Assignment

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Advanced control strategies to exploit the hydropower potential enhancing ancillary services provision to the power system

Electrochemical Hydrophobic Tri-layer Interface Rendered Mechanically Graded Solid Electrolyte Interface for Stable Zinc Metal Anode

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Inversing the actuation cycle of dielectric elastomer actuators for a facial prosthesis

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Scalable constrained optimization

Fair real-time control of energy storage systems in active distribution networks in the presence of uncertainties

The complexity of quantum support vector machines

On the Generalization of Stochastic Gradient Descent with Momentum

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Real-time Personalized Monitoring of Neurological Disorders on Wearable Systems

An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors