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8th International symposium on Computer Science and Intelligent control, ISCSIC 2024

作者： Yang, Ziying Wang, Yanhu Yu, Yao Liu, Ruonan Zhang, Weidong Xie, Wei Shanghai Jiao Tong University Department of Automation Shanghai China

ISBN: (纸本)9798350380286

This paper investigates the control problem of load trajectory tracking in the slung load system of an unmanned aerial vehicle (UAV) in the presence of unknown disturbances. We derive a coordinate-free dynamical model of the system, accounting for disturbances affecting the quadrotor. The backstepping method was used to design the controller of the quadrotor, which ensures that (i) the load accurately tracks the desired trajectory and (ii) the slung load system achieves asymptotic stability even in the presence of disturbances. Simulation and experiment results are presented to validate the controller, and the stability of the system is proven using Lyapunov stability theory. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Application of Fuzzy-based Uncertainty in Cardiac MRI Segmentation

Application of Fuzzy-based Uncertainty in Cardiac MRI Segmen...

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2025 ieee symposium on computational intelligence in Health and Medicine, CIHM 2025

作者： Lin, Qiao Chen, Xin Chen, Chao Jathanna, Nikesh Swoboda, Peter P. Jamil-Copley, Shahnaz Garibaldi, Jonathan M. School of Computer Science University of Nottingham Ningbo China School of Computer Science University of Nottingham United Kingdom Nottingham University Hospitals NHS Trust United Kingdom Leeds Institute of Cardiovascular and Metabolic Medicine University of Leeds United Kingdom

ISBN: (纸本)9798331508333

Cardiac magnetic resonance imaging (MRI) is pivotal in diagnosing cardiac-related diseases. Tissue segmentation from cardiac MRI images is the initial and most crucial step in downstream analyses. However, most current research focuses on designing segmentation models on cardiac MRI to produce segmentation results, without considering the reliability of these outputs. This paper novelty applied fuzzy-based uncertainty to assess the reliability of cardiac MRI segmentation results without access to ground truth images. Experimental results show that class-level uncertainty has a strong linear negative relationship (PE=-0.92) with the true segmentation quality (measured by Dice). This suggests that when ground truth images are unavailable, uncertainty can effectively estimate the cardiac MRI segmentation quality. Furthermore, qualitative analysis with clinicians is conducted to explore the clinical application of fuzzy-based uncertainty. Based on their feedback and comments, class-level uncertainty provides more detailed information and is more suitable to infer the segmentation quality in comparison to other uncertainties. As for the representation of uncertainty, the predicted Dice is the best option compared to other representation methods and is straightforward for clinicians to understand. © 2025 ieee.

关键词： Model predictive control

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PillarMamba: A Lightweight Mamba-based Model for 3D Object Detection 4

PillarMamba: A Lightweight Mamba-based Model for 3D Object D...

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4th ieee International Conference on Digital Twins and Parallel intelligence, DTPI 2024

作者： Liu, Yuhang Ge, Yinji Li, Mengyue Zheng, Guixu Sun, Boyi Wang, Fei-Yue Chinese Academy of Sciences Institute of Automation Beijing China Beijing Jiaotong University School of Mechanical Electronic and Control Engineering Beijing China

ISBN: (纸本)9798350349252

Parallel LiDAR is a novel framework for constructing next-generation intelligent LiDAR systems. 3D object detection serves as a common perception task in parallel LiDAR research. However, current approaches heavily rely on CNNs or Transformers for feature interaction, placing high demands on computational resources and memory. We introduce the evolving Mamba architecture into 3D object detection to address these issues and propose a new PillarMamba network. PillarMamba utilizes a pure Mamba-based backbone composed of multiple stacked BEVMamba blocks. Our experiments on the KITTI dataset demonstrate that PillarMamba can achieve 65.41% mAP in BEV and 59.13% mAP in 3D perspectives. It paves the way for constructing more efficient and accurate detection models, holding significant value for practical applications. © 2024 ieee.

关键词： Object recognition

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A method for determining the analytical solution for Bagley Torvik equations with fractional derivatives 16

A method for determining the analytical solution for Bagley ...

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16th ieee International symposium on Applied computational intelligence and Informatics, SACI 2022

作者： Pasca, Madalina Sofia Caruntu, Bogdan Albu, Adriana Politehnica University Timisoara Mathematics Department Timisoara Romania West University of Timisoara Timisoara Romania Politehnica University Timisoara Department of Automation and Applied Informatics Timisoara Romania

ISBN: (数字)9781665481250

ISBN: (纸本)9781665481250

This paper presents the method called Piecewise Polynomial Least Squares Method (PWPLSM) for determining the approximate analytical solution for Bagley Torvik fractional differential equation. The equation models the deformation resistance characteristics of different polymers, having applicability in various branches of engineering. The paper focuses on the operation of the PWPLSM method and its accuracy. © 2022 ieee.

关键词： Least squares approximations

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Energy Consumption Analysis for Raspberry Pi Based Smart Mirrors and Proposed Solutions 16

Energy Consumption Analysis for Raspberry Pi Based Smart Mir...

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16th ieee International symposium on Applied computational intelligence and Informatics, SACI 2022

作者： Rat, Alexandru Stangaciu, Cristina Micea, Mihai Politechnica University of Timisoara Faculty of Automation and Computers Timisoara Romania Politechnica University of Timisoara Computers and Information Technology Department Timisoara Romania

ISBN: (数字)9781665481250

ISBN: (纸本)9781665481250

This article presents an analysis regarding energy consumption of a type of smart devices, namely smart mirrors using a reference implementation based on Raspberry Pi and providing features like Internet connectivity, access to different applications, voice command and geolocation. This paper includes a comparative study between different software implementations and configurations proposed for the smart mirror. © 2022 ieee.

关键词： Energy utilization

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Automating the Handling Process of a Coffee Machine Using a Robotic Manipulator 15

Automating the Handling Process of a Coffee Machine Using a ...

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15th International symposium on Industrial Electronics and Applications, INDEL 2024

作者： Michalkova, Sona Wojnarowsky, Krystof Kolenyak, Simon Kantor, Matej Arm, Jakub Brno University of Technology Dept. of Control and Instrumentation Brno Czech Republic

ISBN: (纸本)9798350352320

The study RoboCafe explores the automation of a lever-action coffee-making system using a FANUC robotic manipulator controlled by a PLC complying with ISA-88 standards. The robotic arm, equipped with a specialized gripper, is designed to handle various components of the coffee-making system, including operating a lever-action coffee machine and grinder. A virtual simulation of the system was developed to test and validate the system before physical implementation using virtual commissioning techniques. Strength measurement confirmed the robotic arm's capability to exert the required force for coffee machine operation. Using standard industrial communication such as Modbus TCP, the cooperation between heterogenous controllers can be established in case other communication protocol is not supported. © 2024 ieee.

关键词： Grippers

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A Hybrid Decoupled Method For Tertiary Voltage control of Active Distribution Networks

A Hybrid Decoupled Method For Tertiary Voltage Control of Ac...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Sanni, Mubeenah Titilola Pota, Hemanshu Dong, Daoyi Mo, Huadong Univ New South Wales Sch Engn & Informat Technol Canberra ACT Australia

ISBN: (纸本)9781665487689

A tertiary voltage control (TVC) algorithm based on reactive optimal power flow (ROPF) is proposed to obtain reference voltages for pilot points in distribution networks. The algorithm employs a non-linear interior point method and differential evolution to minimise the overall distribution network's system losses. TVC is modelled as a hybrid decoupled optimal power flow problem transformed into two partial duality sub-problems. The reactive power sub problem is modelled as a quadratic programming problem, and the active power sub problem is modelled as a linear programming problem. Numerical simulations are performed using the ieee 123 node distribution feeder to demonstrate the algorithm's efficiency, and it is observed that the system losses are reduced by 29.4 per cent after optimisation. Finally, the method is compared further with other approaches to justify the superiority of the proposed hybrid method for distribution network's loss minimization.

关键词： Differential Evolution Distributed Generation Interior Point Method Optimal Power Flow Tertiary Voltage control

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Voltage control of Distribution Network Based on Parallel control System 3

Voltage Control of Distribution Network Based on Parallel Co...

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3rd ieee International Conference on Digital Twins and Parallel intelligence, DTPI 2023

作者： Wang, Zhiwu Zhao, Xiangyang Zhu, Yuan Yang, Linze Beihang University School of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350318470

With the increasing penetration of renewable energy sources in distribution networks, the node voltage crossing limits caused by distributed generation (DG) has brought a very big challenge to the operation and scheduling of distribution networks. Therefore, this paper constructs a parallel control system for distribution network to guarantee the safe and reliable operation of the actual distribution network system. Firstly, we build an equivalent digital twin of the actual distribution network system based on NI PXI controller;then, proposes a centralized distribution network scheduling model based on second-order cone optimization, and coordinates the centralized optimization model based on the digital twin to determine the best voltage control strategy for the actual distribution network system through computational experiments and evaluation;secondly, improves the voltage control ability of the distribution network by parallel execution and coordinated optimization between the constructed artificial system and the actual system;finally verifies the feasibility and significant advantages of the parallel voltage control system for distribution networks by using the ieee33 distribution network system as an example. © 2023 ieee.

关键词： control systems

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Multiscale Global Prompt Transformer for EEG-Based Driver Fatigue Recognition

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ieee TRANSACTIONS ON automation SCIENCE AND ENGINEERING 2025年 22卷 2700-2711页

作者： Zhao, Pengbo Lian, Cheng Xu, Bingrong Zeng, Zhigang Wuhan Univ Technol Sch Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

Driver fatigue is a critical factor that lead to traffic accidents with a high fatality rate. Electroencephalogram (EEG) is one of the most reliable indicators to objectively assess fatigue status, but recognizing fatigue driving status from it is still an essential and challenging problem. In this paper, we propose a multiscale global prompt Transformer (MsGPT) deep learning model, which can automatically recognize driver fatigue end-to-end. First, we construct an intra-inter-scale cascade framework based on Transformer with a multiscale convolutional patch embedding (MC-PatchEmbed), and guide global-local feature interaction by adding a global prompt token throughout. Second, to efficiently integrate intra-scale and inter-scale feature information, we design a mixed token by aggregating the output from the intra-scale, which includes rich low-level feature information for multiscale. Moreover, a novel learnable query is introduced into multi-head self-attention (MSA) to reduce the computational complexity to linear level. Experiments are conducted on the SEED-VIG dataset and the SADT dataset with both intra-subject and inter-subject settings to evaluate the performance of MsGPT, and the results show that MsGPT greatly outperforms various methods in terms of the classification evaluation metrics of EEG-based fatigue driving. Note to Practitioners-This paper considers the use of raw EEG data to recognize the driver fatigue state. Existing methods mainly rely on manually extracted EEG features and convolutional neural network (CNN) based inference. However, the large intra-individual and inter-individual differences greatly limit the extraction of EEG fatigue features. This paper suggests a multiscale global prompt Transformer (MsGPT) deep learning model. This model leverages a shared weighting mechanism to construct an inter- to intra-scale multiscale framework that can capture refined fatigue features not achievable at a single scale, we incorporate a new Transform

关键词： EEG multiscale learning global prompt learnable query

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An Algorithm to Support the Review Process of a Scientific Research Project Proposal Using ChatGPT 8

An Algorithm to Support the Review Process of a Scientific R...

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8th International symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Rashidov, Aldeniz Department of Automation information and control systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9798350354423

Reviewing scientific research project proposals (SRPPs) is essential for the development of scientific knowledge and innovation. Traditional peer review methods often face challenges such as significant drafting time, subjective evaluations, and a shortage of qualified reviewers, which reduce the quality of reviews. With the development of artificial intelligence, the potential for improving the peer review process is being discovered. This study proposes and evaluates an algorithm to assist the peer review process using ChatGPT. The algorithm aims to optimize the review process by automating the analysis, generating objective scores using weighting coefficients, SWOT analysis and providing feedback on various aspects of project proposals. The study analyses the effectiveness of the algorithm through a SWOT analysis that highlights its strengths, weaknesses, opportunities and threats. The algorithm may be useful for reviewers, researchers and academic institutions seeking to enhance the effectiveness and objectivity of SRPP evaluation. © 2024 ieee.

关键词： Algorithm Artificial intelligence ChatGPT Evaluation Project Review SWOT Analysis

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