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SSRN 2024年

作者： Polo-Rodríguez, Aurora Anguita-Molina, Miguel Ángel Ruiz, Ignacio Rojas Medina-Quero, Javier Department of Computer Engineering Automation and Robotics University of Granada Granada18071 Spain Department of Computer Science University of Jaén Jaén23071 Spain

This work explores the integration of millimetre wave (mmWave) Radar and minimal configuration of Ultra-Wideband (UWB) devices for enhanced tracking of multiple occupants in real domestic environments. Using a low-cost, non-intrusive, and quickly deployable device setup, our approach addresses the challenges of multi-occupant tracking with a focus on privacy and ease of installation. Initially, mmWave Radar identifies the presence of occupants with high precision but lacks individual recognition and limited sensitivity. By incorporating a minimal configuration of UWB (wearable tags and ambient anchors), we include identification through signal strength measurements, bypassing complex localisation needs. In addition, we propose several autoencoder models to fuse data from these diverse sources. Experiments carried out in two real-world domestic settings that involve up to three inhabitants per room showcase the ability of the proposal to combine mmWave and UWB technologies for indoor multioccupant tracking, suggesting promising applications in smart homes, ambient assisted living, and eHealth. © 2024, The Authors. All rights reserved.

关键词： Millimeter waves

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Enhancing Sentiment Analysis on SEED-IV Dataset with Vision Transformers: A Comparative Study 23

Enhancing Sentiment Analysis on SEED-IV Dataset with Vision ...

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Proceedings of the 2023 11th International Conference on Information Technology: IoT and Smart City

作者： Imad Eddine Tibermacine Ahmed Tibermacine Walid Guettala Christian NAPOLI Samuele Russo Department of Computer Automation and Management Engineering Sapienza Unviersity of Rome Italy Department of Computer Science University of Biskra Algeria Department of Computer Automation and Management Engineering Sapienza Unviersity of Rome Italy and Institute for Systems Analysis and computer Science Italian National Research Council Italy and Department of Computational Intelligence Czestochowa University of Technology Poland Department of Psychology Sapienza Unviersity of Rome Italy

ISBN: (纸本)9798400709043

This paper introduces a new approach to emotion classification utilising deep learning models, specifically the Vision Transformer (ViT) model, in the analysis of electroencephalogram (EEG) signals. A dual-feature extraction approach was implemented in our study, utilising Power Spectral Density and Differential Entropy, to analyse the SEED IV dataset. This methodology resulted in the detailed classification of four distinct emotional states. The ViT model, which was originally designed for image processing, has been successfully applied to EEG signal analysis. It demonstrated remarkable performance by attaining a test accuracy of 99.02% with little variance. Notably, it outperformed conventional models like GRUs, LSTMs, and CNNs in this context. The findings of our study indicate that the ViT model has a high level of effectiveness in accurately identifying complex patterns present in EEG data. Specifically, the precision and recall rates achieved by the model surpass 98%, while the F1 score is estimated to be about 98.9%. The results of this study not only demonstrate the efficacy of transformer-based models in analysing cognitive states, but also indicate their considerable potential in improving systems for sympathetic human-computer interaction.

关键词： Classification Deep Learning EEG Signal Analysis Vision Transformer

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Design Pattern for Industrial Control Applications Based on One-Line IEC 61499 Adapter Connections

Design Pattern for Industrial Control Applications Based on ...

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Annual Conference of Industrial Electronics Society

作者： Pranay Jhunjhunwala Polina Ovsiannikova Valeriy Vyatkin Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Computer and Space Engineering Lulea Tekniska Universitet Sweden

IEC 61499 is an emerging standard for distributed automation which requires well-defined design practises to improve development efficiency. In this paper, we extend the one-line engineering design pattern and provide step-by-step guidelines on its implementation keeping in mind key features of Industry 4.0. The one-line design pattern simplifies the modification of the application structure and the addition of new components to the system without disrupting the existing control application. It also enables easy fault identification and debugging of the system. The design pattern was developed and validated in three different use cases that demonstrated the applicability of the pattern.

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LLGS: Unsupervised Gaussian Splatting for Image Enhancement and Reconstruction in Pure Dark Environment

arXiv

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arXiv 2025年

作者： Wang, Haoran Huang, Jingwei Yang, Lu Deng, Tianchen Zhang, Gaojing Li, Mingrui The School of Engineering and Informatics University of Sussex United Kingdom The Department of Automation Engineering University of Electronic Science and Technology of China China The Department of Automation Shanghai Jiao Tong University China The Department of Computer Science Dalian University of Technology China

3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization. However, the original 3D Gaussian Splatting lacks color representation for inputs in low-light environments. Simply using enhanced images as inputs would lead to issues with multi-view consistency, and current single-view enhancement systems rely on pre-trained data, lacking scene generalization. These problems limit the application of 3D Gaussian Splatting in low-light conditions in the field of robotics, including high-fidelity modeling and feature matching. To address these challenges, we propose an unsupervised multi-view stereoscopic system based on Gaussian Splatting, called Low-Light Gaussian Splatting (LLGS). This system aims to enhance images in low-light environments while reconstructing the scene. Our method introduces a decomposable Gaussian representation called M-Color, which separately characterizes color information for targeted enhancement. Furthermore, we propose an unsupervised optimization method with zero-knowledge priors, using direction-based enhancement to ensure multi-view consistency. Experiments conducted on real-world datasets demonstrate that our system outperforms state-of-the-art methods in both low-light enhancement and 3D Gaussian Splatting. © 2025, CC BY-NC-ND.

关键词： Stereo image processing

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A study on the identification of types of cerebral edema by using multi-parametric imaging system 12

A study on the identification of types of cerebral edema by ...

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Optics in Health Care and Biomedical Optics XII 2022

作者： Zhang, Yameng Li, Weitao Qi, Xinping Qian, Zhiyu Department of Computer Engineering Nanjing Institute of Technology Jiangsu Nanjing211167 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211106 China

ISBN: (纸本)9781510657069

Cerebral edema is a potentially fatal disorder and divided into several types. The accurately identifying the type of cerebral edema is vital for the precise treatment. Previous studies have been devoted the multi-model parameters to access the feature cerebral edema. However, few research focused on the models to distinguish the types of cerebral edema. Here, a multi-parameter joint imaging system was developed, which combined laser speckle contrast imaging system (LSCI) and intrinsic optical signals imaging system (IOS). Several parameters such as relative cerebral blood flow (rCBF), concentration changes of oxy-hemoglobin (HbO), deoxy-hemoglobin (HbR), and blood oxygen saturation (sO2) were recorded at the same region of interest (ROI). Vasogenic and cytotoxic cerebral edema models were induced by phenylephrine hydrochloride and vasopressin, respectively. The mice were randomly assigned to 2 groups and 10 individuals in each group. After drug injection, the parameters were collected every 20 minutes within 2 h in vivo. The rCBF in both groups increased gradually within 2 hours throughout the whole process, but the rCBF in the vasogenic group grew substantially faster than it in the cytotoxic group within the first 80 minutes. In the vasogenic group, the concentration changes of HbO and HbR were more pronounced. The data was analyzed by the t-test of an independent sample, and there were significant differences between the parameters of the two types of cerebral edema. It has potential for achieving a classification of cerebral edema. © 2022 SPIE.

关键词： Imaging systems

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Fast Joint Image Compression-Encryption Algorithm used for 3D Reconstruction 24

Fast Joint Image Compression-Encryption Algorithm used for 3...

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24th International Carpathian Control Conference, ICCC 2023

作者： Salih, Omar M. Rostum, Hussam M. Vasarhelyi, Jozsef Siddeq, Mohammed M. University of Miskolc Institute of Automation and Info-Communication Hungary Technical College of Kirkuk Northern Technical University Iraq Northern Technical University Technical College of Kirkuk Computer Engineering Department Kirkuk Iraq

ISBN: (纸本)9798350310221

This paper presents a JPEG-improved algorithm for compression and encryption of 2D structured light images applied in 3D reconstruction. The proposed method incorporates compression and encryption simultaneously to achieve a high compression ratio while adding security without affecting 3D reconstruction. The 2D structured light image is divided into 8×8 blocks, then DCT is applied for each block followed by an optimized JPEG-based quantization matrix. The resulting blocks are merged in a single matrix, and the DC coefficients in each column are subjected to first-order difference to reduce the Min-Max span for fast decoding. The decompression is accomplished reversely, and a fast sequential search method is proposed based on a conventional searching approach. The results showed achieving up to a 98% compression ratio of 2D structured light images while maintaining successful and accurate 3D reconstruction. Moreover, the execution time decreased significantly by (61%-80%). © 2023 IEEE.

关键词： Image compression

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An Economic Feasibility Study for Off-Grid Hybrid Renewable Energy Resources 31

An Economic Feasibility Study for Off-Grid Hybrid Renewable ...

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31st Southern African Universities Power engineering Conference, SAUPEC 2023

作者： Ogunwole, Emmanuel Idowu Krishnamurthy, Senthil Center for Substation Automation and Energy Management Systems Cape Peninsula University of Technology Department of Electrical Electronic and Computer Engineering PO BOX 1906 Symphonyway Cape Town Bellville7535 South Africa

Renewable energy resources (RES) are gaining popularity worldwide. As a result, renewable energy sources (RES) are now considered an alternative source of electric power generation in many communities. Furthermore, using renewable energy sources reduces pollution caused by coal and the release of carbon into the atmosphere by power plants. This article focuses on the economic feasibility of renewable energy resources since it is one of the obstacles in building and executing effective and efficient power generation with RES. An optimizer function of HOMER Pro software was employed in this study to develop a cost-effective power-generating RES configuration. The system uses an IEEE 14-Bus load demand of 259 MW supplied by five generators tested the design system in an IEEE 14-Bus test system with a total load demand of 259 MW supplied by five generators. The loads were classified as critical or non-critical. Three case studies were considered: 1. a case in which all five generators supplied the loads, 2. a case in which one generator was replaced by solar PV with the same generating capacity, and 3. a case in which two generators were replaced by both solar PV and wind turbine respectively. The decrease in net present cost (NPC), Levelized cost (COE), and operating cost (OC) demonstrate the efficacy of the proposed system topologies with various forms of RES. © 2023 IEEE.

关键词： Renewable energy resources

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Distributed Optimization-Based Formation Control: A Dynamic Event-Triggered Approach 42

Distributed Optimization-Based Formation Control: A Dynamic ...

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42nd Chinese Control Conference, CCC 2023

作者： Yu, Hao Yang, Junyi Chen, Tongwen School of Automation Beijing Institute of Technology Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9789887581543

This paper investigates an event-triggered approach for distributed optimization-based formation problems of multi-agent systems (MASs) under directed graphs. A distributed optimization-based algorithm is proposed such that agents can rendezvous around an expected time-varying formation, and at the same time, optimize a global objective function. A novel dynamic event-triggering mechanism is proposed, where a buffer variable is introduced to store the historical local information including the average values of measurement errors over one transmission interval. Then, the closed-loop MAS is proved to be input-to-state exponentially stable with respect to external inputs. Zeno-freeness is guaranteed by a computable minimum interevent time. Moreover, the trade-off between network load and computation complexity is illustrated by comparing two kinds of event-triggered mechanisms based on different signals as inputs to the buffer variables. The effectiveness of the proposed method is verified by numerical examples. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Multi agent systems

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Research on Path Planning of Mobile Robot Based on Reinforcement Learning

Research on Path Planning of Mobile Robot Based on Reinforce...

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2022 Chinese automation Congress, CAC 2022

作者： Ji, Maoyuan Li, Jianxing Li, Shanqiang Liu, Zhenyu Song, Jiang Liu, Lisang Fujian Institute of Engineering Fujian Industrial Automation Technology Research and Development Center Fuzhou China Fujian Institute of Engineering Department of Computer Science and Mathematics Fuzhou China

ISBN: (纸本)9781665465335

With the continuous change of artificial intelligence technology, the study of path planning for mobile robots is no longer limited to traditional path algorithms. Reinforcement learning, as an artificial intelligence algorithm with excellent performance in the field of path planning, has also gradually become the object of research on path planning. In order to find a fast path from the starting point to the end point of a mobile robot in a complex environment, reinforcement learning is used to find a valid path by sensing the environment and continuously receiving rewarding feedback through a method of trial and error learning like humans. Therefore, this paper selects two algorithms to verify their effectiveness on the basis of building a two-dimensional grid map. The final experimental results show that both reinforcement learning algorithms can eventually avoid obstacles and plan a valid path in a complex environment through continuous learning iterations. Q-Learning also reduces the path distance by 10% and the number of convergence iterations by 82% compared to Sarsa. © 2022 IEEE.

关键词： Reinforcement learning

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Visual SLAM with a Multi-Modal Semantic Framework for the Visually Impaired Navigation-Aided Device 8

Visual SLAM with a Multi-Modal Semantic Framework for the Vi...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Li, Shaohu Gu, Jason Feng, Ying Institute of Advanced Technology University of Science and Technology of China Hefei230031 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada College of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

Visual Simultaneous Localization and Mapping (VSLAM) based on image feature points often contains feature points on non-stationary objects in dynamic scenes, resulting in poor localization performance. Recent research has improved VSLAM performance by removing dynamic feature points utilizing optical flow, deep learning, or multi-view geometry, however, the volume of data makes real-time operation challenging. In this study, we propose a multimodal framework for semantic VSLAM. To eliminate dynamic feature points, the system effectively blends object detection, instance segmentation, and geometry modules. To ensure high-precision pose estimation and quick back-end optimization, we exclusively use object detection in the front-end of VSLAM to mask dynamic feature points. In the keyframes of the local map, semantic segmentation is utilized to remove dynamic feature points, and an effective geometric module is employed to assess the dynamic consistency of objects that are challenging to categorize. Therefore, more feature points are retained, and the running speed is also ensured. Evaluations of the system on public datasets and in the real world show that it improves the accuracy and stability of VSLAM in dynamic environments. © 2023 IEEE.

关键词： Object detection

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