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Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-based Sensors

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Traffic Signal Control for Large-Scale Urban Traffic Network...

International Conference on Control and Automation (ICCA)

作者： Jiho Park Tong Liu Chieh Wang Hong Wang Qichao Wang Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA Oak Ridge National Laboratory Oak Ridge TN USA National Renewable Energy Laboratory Computational Science Center Golden CO USA

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

关键词： Energy consumption Urban areas Decentralized control Data processing Real-time systems Sensors Delays

Arc-to-line frame registration method for ultrasound and photoacoustic image-guided intraoperative robot-assisted laparoscopic prostatectomy

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arXiv 2023年

作者： Song, Hyunwoo Yang, Shuojue Wu, Zijian Moradi, Hamid Taylor, Russell H. Kang, Jin U. Salcudean, Septimiu E. Boctor, Emad M. Department of Computer Science Whiting School of Engineering The Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering Whiting School of Engineering The Johns Hopkins University BaltimoreMD21218 United States Laboratory for Computational Sensing and Robotics The Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

Purpose: To achieve effective robot-assisted laparoscopic prostatectomy, the integration of transrectal ultrasound (TRUS) imaging system which is the most widely used imaging modality in prostate imaging is essential. However, manual manipulation of the ultrasound transducer during the procedure will significantly interfere with the surgery. Therefore, we propose an image co-registration algorithm based on a photoacoustic marker (PM) method, where the ultrasound/photoacoustic (US/PA) images can be registered to the endoscopic camera images to ultimately enable the TRUS transducer to automatically track the surgical instrument. Methods: An optimization-based algorithm is proposed to co-register the images from the two different imaging modalities. The principle of light propagation and an uncertainty in PM detection were assumed in this algorithm to improve the stability and accuracy of the algorithm. The algorithm is validated using the previously developed US/PA image-guided system with a da Vinci surgical robot. Results: The target-registration-error (TRE) is measured to evaluate the proposed algorithm. In both simulation and experimental demonstration, the proposed algorithm achieved a sub-centimeter accuracy which is acceptable in practical clinics (i.e., 1.15 ± 0.29 mm from the experimental evaluation). The result is also comparable with our previous approach (i.e., 1.05 ± 0.37 mm), and the proposed method can be implemented with a normal white light stereo camera and doesn’t require highly accurate localization of the PM. Conclusion: The proposed arc-to-line based frame registration algorithm that transform between the camera and the TRUS imaging frames can allow simple yet efficient integration of commercial US/PA imaging system into the laparoscopic surgical setting, and contribute to the image-guided surgical intervention applications. © 2023, CC BY.

关键词： Ultrasonic imaging

A Miniaturised Camera-based Multi-Modal Tactile Sensor

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arXiv 2023年

作者： Althoefer, Kaspar Ling, Yonggen Li, Wanlin Qian, Xinyuan Lee, Wang Wei Qi, Peng Queen Mary University of London London United Kingdom Tencent Robotics X Lab Shenzhen China Beijing China The Department of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai China

In conjunction with huge recent progress in camera and computer vision technology, camera-based sensors have increasingly shown considerable promise in relation to tactile sensing. In comparison to competing technologies (be they resistive, capacitive or magnetic based), they offer super-high-resolution, while suffering from fewer wiring problems. The human tactile system is composed of various types of mechanoreceptors, each able to perceive and process distinct information such as force, pressure, texture, etc. Camera-based tactile sensors such as GelSight mainly focus on high-resolution geometric sensing on a flat surface, and their force measurement capabilities are limited by the hysteresis and non-linearity of the silicone material. In this paper, we present a miniaturised dome-shaped camera-based tactile sensor that allows accurate force and tactile sensing in a single coherent system. The key novelty of the sensor design is as follows. First, we demonstrate how to build a smooth silicone hemispheric sensing medium with uniform markers on its curved surface. Second, we enhance the illumination of the rounded silicone with diffused LEDs. Third, we construct a force-sensitive mechanical structure in a compact form factor with usage of springs to accurately perceive forces. Our multi-modal sensor is able to acquire tactile information from multi-axis forces, local force distribution, and contact geometry, all in real-time. We apply an end-to-end deep learning method to process all the information. © 2023, CC BY.

关键词： Silicones

Evaluating Cyber-Crime Using Machine Learning and AI Approach for Environmental Sustainability 2nd

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Evaluating Cyber-Crime Using Machine Learning and AI Approac...

2nd International Conference on Sustainable Development Using Machine Learning, Artificial Intelligence, and IoT, ICSD 2024

作者： Chauhan, Ritu Mehtar, Khushi Kaur, Harleen Alankar, Bhavya Artificial Intelligence and IOT Lab Center for Computational Biology and Bioinformatics Amity University Uttar Pradesh Noida India Amity Institute of Biotechnology Amity University Uttar Pradesh Noida India Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India

ISBN: (纸本)9783031717284

The online world has become an essential part of everyday life in India due to its fast expansion and technical improvements. But as technology has advanced, cyber-crimes have also increased dramatically, posing serious risks to the economy, security, and privacy. This research examines the intricate terrain of cybercrimes targeting minors in India, scrutinizing more than 16 lakh cases that have been documented during the three years preceding this one. The study takes an extensive approach, applying machine learning modelling such as Gradient Boosting, AdaBoost, Random Forest, Gaussian Naive Bayes, Bernoulli Naive Bayes, Linear SVM, Logistic Regression, and Gradient Boosting in conjunction with exploratory assessment of data. The findings show different accuracy rates;Random Forest, Gradient Boosting, Linear SVM, and Gaussian Naive Bayes all show an impressive 88% accuracy. AdaBoost and Logistic Regression reach 75%, but Bernoulli Naive Bayes comes in lower at 62%. The comprehension of computational interconnections is improved with correlation matrices. This thorough analysis provides important insights for academics, policymakers, and stakeholders in the field of child cybersecurity by exposing common cyber threats targeting minors and highlighting the role that algorithms for learning may play in detecting and averting these risks for environmental sustainability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

Markerless Sagittal Gait Analysis of Cerebral Palsy in Children Using Pose Estimation Techniques

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Markerless Sagittal Gait Analysis of Cerebral Palsy in Child...

Innovation in Computing and Engineering (ICE), International Conference on

作者： Vinay Kumar Vats Chandra Prakash Amandeep Kaur Rajesh Kumar Computer Science and Engineering National Institute of Technology Delhi India Computational Intelligence and Smart Motion Research (CISMR) Lab SVNIT Surat India Malaviya National Institute of Technology Jaipur India Department of Human Anatomy and Physiology Faculty of Health Sciences University of Johannesburg Johannesburg South Africa

ISBN: (数字)9798350380460

ISBN: (纸本)9798350380477

Cerebral Palsy (CP) is a neurological disorder affecting children’s motor function and posture. Early detection and monitoring of Cerebral palsy is crucial for effective intervention and improved quality of life. Gait analysis is a critical tool for assessing motor function in children with cerebral palsy, often requiring controlled environments and markers for accuracy. Markerless gait analysis has emerged as a promising tool for objectively evaluating gait abnormalities in children with CP. In this study, we propose a markerless methodology utilising pose estimation to analyse gait patterns from sagittal video recordings captured in unconstrained environments. The dataset consists of 49 children, including 10 typically developing children and 39 with cerebral palsy, focusing on side-view videos for the analysis. Given the motor disabilities of these children, conducting gait analysis in a constrained environment can alter their natural walking patterns, making our approach particularly advantageous. Then we identify the key gait events, heel strike and toe-off, to distinguish gait between cycles by tracing knee joint movements. This technique demonstrates the potential for practical, non-invasive gait assessment in natural settings, offering insights into the distinct gait characteristics of children with cerebral palsy compared to their typically developing peers.

关键词： Legged locomotion Neurological diseases Cerebral palsy Technological innovation Pose estimation Motors Motion control Gait recognition Video recording Monitoring

Automatic Search for Photoacoustic Marker Using Automated Transrectal Ultrasound

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arXiv 2023年

作者： Wu, Zijian Moradi, Hamid Yang, Shuojue Song, Hyunwoo Boctor, Emad M. Salcudean, Septimiu E. Johns Hopkins University Laboratory for Computational Sensing and Robotics BaltimoreMD United States University of British Columbia Dept. of Electrical and Computer Engineering VancouverBC Canada University of Texas at Austin Walker Department of Mechanical Engineering AustinTX United States Johns Hopkins University Dept. of Computer Science BaltimoreMD United States

Real-time transrectal ultrasound (TRUS) image guidance during robot-assisted laparoscopic radical prostatectomy has the potential to enhance surgery outcomes. Whether conventional or photoacoustic TRUS is used, the robotic system and the TRUS must be registered to each other. Accurate registration can be performed using photoacoustic (PA markers). However, this requires a manual search by an assistant [19]. This paper introduces the first automatic search for PA markers using a transrectal ultrasound robot. This effectively reduces the challenges associated with the da Vinci-TRUS registration. This paper investigated the performance of three search algorithms in simulation and experiment: Weighted Average (WA), Golden Section Search (GSS), and Ternary Search (TS). For validation, a surgical prostate scenario was mimicked and various ex vivo tissues were tested. As a result, the WA algorithm can achieve 0.53o ± 0.30o average error after 9 data acquisitions, while the TS and GSS algorithm can achieve 0.29° ± 0.31° and 0.48o ± 0.32o average errors after 28 data acquisitions. © 2023, CC BY.

关键词： Urology

Active Vibration Reduction for the Autonomous Observation Mechanism

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Active Vibration Reduction for the Autonomous Observation Me...

Control Technology and Applications (CCTA),

作者： Fatemeh Rekabi-Bana Mahmood Saadat Nahid Kalantaryardebily Martin Stefanec Laurenz A. Fedotoff Honghao Pan Tomáš Krajník Thomas Schmickl Farshad Arvin Department of Computer Science Swarm & Computational Intelligence Laboratory (SwaCIL) Durham University UK Faculty of Engineering Mechanics Virginia Tech Blacksburg Virginia United States of America Artificial Life Lab University of Graz Austria Faculty of Electrical Engineering Czech Technical University Czechia

ISBN: (数字)9798350370942

ISBN: (纸本)9798350370959

This paper presents a method applied for vibration reduction in an autonomous mechanism developed for robot-insect interaction. The mechanism performs continuous data collection of honeybee behaviour within a living honeybee colony. To ensure sufficient quality of the observations, the system has to be installed in proximity to the hive. However, as honeybees are particularly sensitive to vibrations, it is important to keep the vibrations produced by the mechanism below the values that can disturb the natural behaviour of the bees. Furthermore, avoiding vibrations improves the gathered data quality, decreases the maintenance frequency and prolonges the system service life. In this paper, we present the robotic observation mechanism’s development process of vibration control. The subspace identification method is applied to determine a model utilised to design a controller to actively reduce the resulting vibration while preserving the position tracking accuracy. The results of the experiments demonstrate a reduction of about 10dB in the vibration after applying the suggested controller.

关键词： Vibrations Power measurement Mechatronics Process control Vibration measurement Aerospace electronics Position measurement

Classification of Breast Thermal Images into Healthy/Cancer Group Using Pre-Trained Deep Learning Schemes

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Classification of Breast Thermal Images into Healthy/Cancer ...

2022 International Conference on Machine Learning and Data Engineering, ICMLDE 2022

作者： Kadry, Seifedine Crespo, Rubén González Herrera-Viedma, Enrique Krishnamoorthy, Sujatha Rajinikanth, Venkatesan Faculty of Applied Computing and Technology Noroff University College Kristiansand94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de la Rioja Andalusia26006 Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India

In the women's community, Breast Cancer (BC) is a severe disease. The World Health Organization reported in 2020 that 2.26 million deaths occur due to BC. BC is curable if detected early. Since thermal imaging is non-invasive and supports disease detection, it is commonly used in clinics. Compared to other methods, it keeps BC early and accurate. The proposed work aims to evaluate the performance of the Pretrained Deep-Learning Methods (PDLM) in detecting BC using the thermal images collected from the benchmark dataset. It includes the following stages: primary image processing, deep feature mining, handcrafted feature mining, feature optimization using Firefly-Algorithm (FA), classification and validation. Visual lab thermal images were used in the study. The investigational outcome of this study authenticates that the VGG16, along with the DT, provides better detection accuracy (95.5%) compared to other classifiers used in this study. To justify the significance of the implemented technique, the proposed work not only improved accuracy, but also improved precision, sensitivity, specificity, and F1-Scores. © 2023 The Authors. Published by Elsevier B.V.

关键词： Classification (of information)

Sim-to-Real for Soft Robots using Differentiable FEM: Recipes for Meshing, Damping, and Actuation

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arXiv 2022年

作者： Dubied, Mathieu Michelis, Mike Y. Spielberg, Andrew Katzschmann, Robert K. Soft Robotics Lab. Department of Mechanical and Process Engineering ETH Zurich Switzerland Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA United States

An accurate, physically-based, and differentiable model of soft robots can unlock downstream applications in optimal control. The Finite Element Method (FEM) is an expressive approach for modeling highly deformable structures such as dynamic, elastomeric soft robots. In this paper, we compare virtual robot models simulated using differentiable FEM with measurements from their physical counterparts. In particular, we examine several soft structures with different morphologies: a clamped soft beam under external force, a pneumatically actuated soft robotic arm, and a soft robotic fish tail. We benchmark and analyze different meshing resolutions and elements (tetrahedra and hexahedra), numerical damping, and the efficacy of differentiability for parameter calibration using a simulator based on the fast Differentiable Projective Dynamics (DiffPD). We also advance FEM modeling in application to soft robotics by proposing a predictive model for pneumatic soft robotic actuation. Through our recipes and case studies, we provide strategies and algorithms for matching real-world physics in simulation, making FEM useful for soft robots. © 2022, CC BY.

关键词： Finite element method