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ISSN: 2949-8554

Bilateral co-transfer for unsupervised domain adaptation

Labeled data scarcity of an interested domain is often a serious problem in machine learning. Leveraging the labeled data from other semantic-related yet co-variate shifted source domain to facilitate...

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A comprehensive survey of robust deep learning in computer vision

Deep learning has presented remarkable progress in various tasks. Despite the excellent performance, deep learning models remain not robust, especially to well-designed adversarial examples, limiting...

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Consensus of networked control multi-agent systems using a double-layer encryption scheme

This paper addresses the decentralized consensus problem for a system of multiple dynamic agents with remote controllers via networking, known as a networked control multi-agent system (NCMAS). It presents...

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Leveraging on few-shot learning for tire pattern classification in forensics

This paper presents a novel approach for tire-pattern classification, aimed at conducting forensic analysis on tire marks discovered at crime scenes. The classification model proposed in this study...

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Matrix pencil based robust control for feedforward systems with event-triggered communications and sensor/actuator faults

In this paper we address the issue of output-feedback robust control for a class of feedforward nonlinear systems. Essentially different from the related literature, the feedback/input signals are corrupted...

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MsFireD-Net: A lightweight and efficient convolutional neural network for flame and smoke segmentation

With the rising frequency and severity of wildfires across the globe, researchers have been actively searching for a reliable solution for early-stage forest fire detection. In recent years, Convolutional...

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Non-intrusive soil carbon content quantification methods using machine learning algorithms: A comparison of microwave and millimeter wave radar sensors

Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification, making it a significant carbon source for soil. Applying biochar to soil is a carbon-negative process that...

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Reachable set estimation for discrete-time Markovian jump neural networks with unified uncertain transition probability

This paper focuses on the reachable set estimation for Markovian jump neural networks with time delay. By allowing uncertainty in the transition probabilities, a framework unifies and enhances the generality...

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Adaptive recurrent neural network for uncertainties estimation in feedback control system

In this paper, a recurrent neural network (RNN) is used to estimate uncertainties and implement feedback control for nonlinear dynamic systems. The neural network approximates the uncertainties related...

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A generic framework for qualifications of digital twins in maintenance

Digital twins have emerged as a promising technology for maintenance applications, enabling organizations to simulate and monitor physical assets to improve their performance. In Operation and Maintenance...

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Error reachable set based stabilization of switched linear systems with bounded peak disturbances

This paper investigates the error reachable set based stabilization problem for a class of discrete-time switched linear systems with bounded peak disturbances under persistent dwell-time (PDT) constraint....

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Robust adaptive estimator based on a novel objective function—Using the L1-norm and L0-norm

To fully take advantage of LMS, LMAT, and SELMS, a novel adaptive estimator using the L1-norm and L0-norm of the estimated error is proposed in this paper. Then based on minimizing the mean-square deviation...

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2-D distributed pose estimation of multi-agent systems using bearing measurements

This article studies distributed pose (orientation and position) estimation of leader–follower multi-agent systems over κ-layer graphs in 2-D plane. Only the leaders have access to their orientations...

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Distributed computations for large-scale networked systems using belief propagation

This paper introduces several related distributed algorithms, generalised from the celebrated belief propagation algorithm for statistical learning. These algorithms are suitable for a class of computational...

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Practical prescribed-time tracking control for uncertain strict-feedback systems with guaranteed performance under unknown control directions

In this paper, we consider the practical prescribed-time performance guaranteed tracking control problem for a class of uncertain strict-feedback systems subject to unknown control direction. Due to...

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Evolutionary games and spatial periodicity

Spatial interactions are considered an important factor influencing a variety of evolutionary processes that take place in structured populations. It still remains an open problem to fully understand...

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Towards cognitive navigation: A biologically inspired calibration mechanism for the head direction cell network

To derive meaningful navigation strategies, animals have to estimate their directional headings in the environment. Accordingly, this function is achieved by the head direction cells that were found...

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Practical bipartite consensus for multi-agent systems: A barrier function-based adaptive sliding-mode control approach

This paper is concerned with bipartite consensus tracking for multi-agent systems with unknown disturbances. A barrier function-based adaptive sliding-mode control (SMC) approach is proposed such that...

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Spline adaptive filtering algorithm based on different iterative gradients: Performance analysis and comparison

Two novel spline adaptive filtering (SAF) algorithms are proposed by combining different iterative gradient methods, i.e., Adagrad and RMSProp, named SAF-Adagrad and SAF-RMSProp, in this paper. Detailed...

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Autonomous exploration using UWB and LiDAR

In autonomous exploration, a robot navigates itself in an unknown environment while building a 2D map of the environment. This is typically done using a LiDAR sensor, which however is susceptible to...

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Sampled-data control through model-free reinforcement learning with effective experience replay

Reinforcement Learning (RL) based control algorithms can learn the control strategies for nonlinear and uncertain environment during interacting with it. Guided by the rewards generated by environment,...

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Cost-effective distributed FTFC for uncertain nonholonomic mobile robot fleet with collision avoidance and connectivity preservation

In this paper, the fault-tolerant formation control (FTFC) problem is investigated for a group of uncertain nonholonomic mobile robots with limited communication ranges and unpredicted actuator faults,...

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Model predictive control for water management and energy security in arid/semiarid regions

This paper aims to develop a realistic operational optimal management of a water supply system in an arid/semiarid region under climate change conditions. The developed model considers the dynamic variation...

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On the new era of automation and intelligence

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A survey on computationally efficient neural architecture search

Neural architecture search (NAS) has become increasingly popular in the deep learning community recently, mainly because it can provide an opportunity to allow interested users without rich expertise...

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