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Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.

Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.

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  1. Brunel University Research Archive

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ENHANCING OPERATIONAL EFFICIENCY IN MUMBAI’S AIRPORT DEPARTURE TERMINAL: A HYBRID SIMULATION MODELING APPROACH See

...

DAF-DETR: A dynamic adaptation feature transformer for enhanced object detection in unmanned aerial vehicles See

Object detection in complex environments is challenged by overlapping objects, complex spatial relationships, and dynamic variations in target scales. To address these challenges, the Dynamic Adaptation Feature DEtection TRansformer (DAF-DETR) is proposed as a novel transformer-based model optimized for&#x...

Proportional-Integral-Observer-Based Fusion Estimation for Artificial Neural Networks: Implementing a One-Bit Encoding Scheme See

This article is concerned with the proportional-integral-observer (PIO)-based fusion estimation problem for a class of artificial neural networks (ANNs) equipped with multiple sensors, which are constrained by bandwidth and subjected to unknown-but-bounded noises (UBBNs). For the purpose of efficient ...

Investigation on the integrated approach to design and ultraprecision machining of freeform surfaced optics and its implementation perspectives See

Over the last two decades or so, high precision freeform surfaced components and devices have been drawing the increasing attention by the industry due to their potentials in fulfilling demands for various engineering and consumers applications, such as consumer electronics, biomedical engin...

Noise-tolerant fixed-time leader-follower consensus controller design for multi-agent systems via fuzzy-neural-network See

The leader-follower consensus control problem in multi-agent systems (MASs) is critical and has received significant attention. However, the simultaneous achievement of fixed-time stability and robustness is often challenging in MASs due to their inherent complexity and uncertainty. This paper develop...

A Novel Pairwise Domain-Adaptation-Assisted Dual-Task Learning Approach to Coprediction of Robotic Machining Efficiency and Quality in New Parameter Spaces See

Accurate prediction of material removal depth and averaged surface roughness is crucial for evaluating the performance of robotic belt grinding (RBG). Nevertheless, the machining parameters of RBG across different spaces exhibit various data distributions, which often results in prediction shifts ...

Neural-Network-Based Recursive State Estimation for Nonlinear Networked Systems With Binary-Encoding Mechanisms See

This work addresses the problem of recursive state estimation for networked control systems with unknown nonlinearities and binary-encoding mechanisms (BEMs). To enhance transmission reliability and reduce network resource consumption, BEMs are used to convert measurement signals into binary bit strin...

BR-MTFL: A Novel Byzantine Resilience-Enhanced Multitask Federated Learning Framework for High-Speed Train Fault Diagnosis See

In high-speed train systems deployed across diverse geographical regions, robust fault diagnosis techniques are essential for ensuring operational safety. This article proposes the Byzantine resilience-enhanced multitask federated learning (BR-MTFL) framework, a novel framework tailored for the complexities of&...

Privacy-preserving distributed optimization for economic dispatch in smart grids See

This paper discusses a distributed economic dispatch problem (EDP) of smart grids while preventing sensitive information from being leaked during the communication process. In response to the problem, a novel privacy-preserving distributed economic dispatch strategy is developed via adding an exp...

Becoming BAME: Social identities and racialized terminology in the UK See

...

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Discover

Author
  • 714 Landsberg, G
  • 714 Lenzi, P
  • 714 Longo, E
  • 714 Moroni, L
  • 714 Nayak, A
  • 714 Onel, Y
  • 714 Organtini, G
  • 714 Pelliccioni, M
  • 714 Richman, J
  • 714 Silvestris, L
  • . < previous next >
Subject
  • 273 CMS
  • 265 Physics
  • 219 Science & Technology
  • 164 Hadron-Hadron scattering (experim...
  • 159 COVID-19
  • 124 machine learning
  • 121 deep learning
  • 105 artificial intelligence
  • 101 Physical Sciences
  • 91 China
  • . next >
Date issued
  • 28181 2000 - 2026
  • 1232 1900 - 1999
  • 3 1830 - 1899
Library (c) Brunel University. Updated: December 19th,2023

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