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Electrical and computer engineering Researches (ICECER), International Conference on

作者： Muteb Aljasem Mustafa Alhababi Ali Javed Zaid Aldoulah Mohammed Abouheaf Mohammad Mayyas Wasseem Al-Rousan Robotics Engineering Bowling Green State University Bowling Green OH MI USA Electrical and Computer Engineering Wayne State University Detroit MI USA Department of Software Engineering University of Engineering and Technology Taxila Pakistan Electrical and Electronics Engineering Alasala colleges Dammam Saudi Arabia Department of Engineering Technology Hamilton Miami University OH MI USA Department of Electrical Engineering Philadelphia University Amman Jordan

ISBN: (数字)9798331539733

ISBN: (纸本)9798331539740

Chronic wounds represent a significant global healthcare challenge, affecting millions of individuals and leading to substantial financial burdens. Accurate classification of chronic wounds is crucial for guiding effective treatment strategies, improving patient outcomes, and reducing healthcare costs. However, existing methods in chronic wound classification predominantly focus on binary classification, with limited success in multi-class scenarios. Consequently, there is a need for diagnostic solutions that can reliably classify multiple wound types. To overcome these challenges, we present a novel feature concatenation-based deep learning method for reliable multiclass classification of chronic wounds. Specifically, we employed the DenseNet121 and XceptionNet models for generating effective and compact feature maps that are then passed to a Multilayer perceptron Classifier to accurately identify different types of wounds. The ability of DenseNet121 to truncate redundant features and XceptionNet to handle complex features with fewer computational resources allows us to generate compact and efficient feature maps. We evaluated the performance of our method using the publicly available AZH and Medetec datasets, as well as their augmented versions. Multiple augmentation techniques were employed to increase sample size and diversity, addressing overfitting and class imbalance issues. A rigorous experimental study performed on the AZH, Medetec, and augmented collections demonstrates the effectiveness of our method for multiclass wound classification.

关键词： Deep learning Costs Accuracy Computational modeling Medical services Wounds Multilayer perceptrons Computational efficiency Reliability Overfitting

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A Miniaturised Camera-based Multi-Modal Tactile Sensor

arXiv

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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

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A Miniaturised Camera-based Multi-Modal Tactile Sensor

A Miniaturised Camera-based Multi-Modal Tactile Sensor

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IEEE International Conference on robotics and Automation (ICRA)

作者： Kaspar Althoefer Yonggen Ling Wanlin Li Xinyuan Qian Wang Wei Lee Peng Qi The Centre for Advanced Robotics @ Queen Mary (ARQ) Queen Mary University of London London United Kingdom Tencent Robotics X Lab Shenzhen China Beijing Institute for General Artificial Intelligence (BIGAI) 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 cam-era 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.

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Prototype of Turbine Propulsion System with Controllable Thrust Vector for Long-Range Unmanned VTOL Aircraft 21st

Prototype of Turbine Propulsion System with Controllable Thr...

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21st Polish Control Conference, PCC 2023

作者： Czyba, Roman Lemanowicz, Marcin Domin, Jaroslaw Grzybowski, Jacek Stępień, Izabela Ungier, Lukasz Rosiek, Radoslaw Bialas, Piotr Niemiec, Michal Department of Automatic Control and Robotics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology ul. Akademicka 16 Gliwice44-100 Poland Department of Chemical Engineering and Process Design Faculty of Chemistry Silesian University of Technology ul. Ks. M. Strzody 7 Gliwice44-100 Poland Department of Mechatronics Faculty of Electrical Engineering Silesian University of Technology ul. Akademicka 10a Gliwice44-100 Poland

ISBN: (纸本)9783031351723

The aim of the project was to build a prototype of a turbine drive with a controllable thrust vector for a long-range vertical take-off and landing (VTOL) aircraft. The construction of the prototype required the development of a vectoring system for the tail propulsion system and a dedicated VTOL aircraft stabilization and control system. The prototype of the turbine drive system was based on energy-efficient electric motors. Research also involved modeling the turbine propulsion aerodynamics with usage of computational fluid dynamics (CFD) analysis. As a result of the design stage, a prototype of the propulsion system was created, on which flight tests were carried out. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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Gone with the Wind: Nonlinear Guidance for Small Fixed-Wing Aircraft in Arbitrarily Strong Windfields

Gone with the Wind: Nonlinear Guidance for Small Fixed-Wing ...

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American Control Conference

作者： Luca Furieri Thomas Stastny Lorenzo Marconi Roland Siegwart Igor Gilitschenski Laboratory of Automation and Robotics Department of Electronics Computer Science and Systems University of Bologna Italy Autonomous Systems Lab Department of Mechanical & Processing Engineering Swiss Federal Institute of Technology (ETH Zurich) Switzerland

ISBN: (纸本)9781509045839

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this paper we present a principled nonlinear guidance strategy, addressing this problem. More broadly, we propose a methodology for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

关键词： Arbitrarily Strong Windfields Fixed wing aircraft Guidance Wind Wings Unmanned Aerial Vehicle low speed level control vehicle visual tracking wall coping nonlinearity Platform

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Microscopic image segmentation using quantum inspired evolutionary algorithm

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Journal of Advanced Microscopy Research 2015年第3期10卷 164-173页

作者： Choudhury, Alokeparna Samanta, Sourav Dey, Nilanjan Ashour, Amira S. Balas-Timar, Dana Gospodinov, Mitko Gospodinova, Evgeniya Department of Computer Science and Engineering University Institute of Technology Burdwan West Bengal713104 India Department of Information Technology Techno India College of Technology Kolkata700156 India Department of Electronics and Electrical Communications Engineering Faculty of Engineering Tanta University 31527 Egypt Aurel Vlaicu University of Arad Arad310130 Romania Institute of Systems Engineering and Robotics Bulgarian Academy of Sciences Sofia1113 Bulgaria

Image segmentation has became an important research area for various medical imaging fields. The automated complex analytical process makes it a huge time consuming procedure. The intention to microscopic images segmentation is to extract the cellular, nuclear or tissue components. This is considered a challenging process due to the large variations of features of these components (size, shape, orientation or texture). In this paper, a novel approach to deal with rats' microscopic hippocampus images segmentation based on the hybrid evolutionary strategy (ES) is proposed. The proposed work used the quantum-inspired evolutionary algorithm (QIEA) to establish the optimal level for the multilevel thresholding. The QIEA depends on both quantum and evolutionary computing. An intensive works for automatic hippocampus segmentation is performed on a database of 179 images. The acquired results have demonstrated that the proposed algorithm provides superior segmentation with eight levels (L = 8), that offer the highest correlation between the original and the corresponding segmented image. © Copyright 2015 American Scientific Publishers All rights reserved.

关键词： Evolutionary algorithms

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Investigation of fuzzy models for the valuation of residential premises using the KEEL tool

Investigation of fuzzy models for the valuation of residenti...

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8th International Conference on Hybrid Intelligent Systems, HIS 2008

作者： Lasota, Tadeusz Mazurkiewicz, Jacek Trawinski, Bogdan Trawinski, Krzysztof Agricultural University of Wroclaw Faculty of Environmental Engineering and Geodesy C.K. Norwida 25/27 50-375 Wroclaw Poland Wroclaw University of Technology Institute of Computer Engineering Control and Robotics Wybrzeze S. Wyspianskiego 27 50-370 Wroclaw Poland Wroclaw University of Technology Institute of Applied Informatics Wybrzeze S. Wyspianskiego 27 50-370 Wroclaw Poland Wroclaw University of Technology Faculty of Electronics Wybrzeze S. Wyspianskiego 27 50-370 Wroclaw Poland

ISBN: (纸本)9780769533261

A series of experiments aimed to generate and learn fuzzy models for the valuation of residential premises was conducted using the KEEL tool (Knowledge Extraction based on Evolutionary Learning). Four regression and four post-processing algorithms were applied to several data sets. They referred to sales/purchase transactions of residential premises, which were derived from the cadastral system and the registry of real estate transactions. The results proved the usefulness of the tool to carry out laborious and tedious investigation in a relatively short time. Further research is needed to determine to what extent data coming from such sources allow to build the real estate valuation models. © 2008 IEEE.

关键词： Housing

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Fully implantable and battery-free wireless optoelectronic system for modulable cancer therapy and real-time monitoring

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npj Flexible electronics 2023年第1期7卷 119-130页

作者： Kiho Kim In Sik Min Tae Hee Kim Do Hyeon Kim Seungwon Hwang Kyowon Kang Kyubeen Kim Sangun Park Jongmin Lee Young Uk Cho Jung Woo Lee Woon-Hong Yeo Young Min Song Youngmee Jung Ki Jun Yu Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic EngineeringYonsei University50 Yonsei-roSeodaemun-guSeoul 03722Republic of Korea Center for Biomaterials Biomedical Research InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Fusion Research and Collaboration Biomedical Research InstituteSeoul National University HospitalSeoul 03080Republic of Korea School of Electrical Engineering and Computer Science(EECS) Gwangju Institute of Science and Technology(GIST)Gwangju 61005Republic of Korea PA1 Foundry BusinessSamsung Electronics1 Samsungjeonja-roHwaseong-siGyeonggi-doRepublic of Korea R&D Center DNA Lab PharmaresearchSeongnam 13486Republic of Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoul 136-705Republic of Korea School of Materials Science and Engineering Energy Materials for Soft Electronics LaboratoryPusan National UniversityBusan 46241Republic of Korea IEN Center for Human-Centric Interfaces and Engineering and George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Robotics and Intelligent Machines Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for MaterialsNeural Engineering CenterGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering YU-Korea Institute of Science and Technology(KIST)InstituteYonsei University50Yonsei-roSeodaemun-guSeoul 03722Republic of Korea

Photodynamic therapy(PDT)is attracting attention as a next-generation cancer treatment that can selectively destroy malignant tissues,exhibit fewer side effects,and lack pain during *** PDT systems have recently been developed to resolve the issues of bulky and expensive conventional PDT systems and to implement continuous and repetitive *** implantable PDT systems,however,are not able to perform multiple functions simultaneously,such as modulating light intensity,measuring,and transmitting tumor-related data,resulting in the complexity of cancer ***,we introduce a flexible and fully implantable wireless optoelectronic system capable of continuous and effective cancer treatment by fusing PDT and hyperthermia and enabling tumor size monitoring in *** system exploits micro inorganic light-emitting diodes(μ-LED)that emit light with a wavelength of 624 nm,designed not to affect surrounding normal tissues by utilizing a fully programmable light intensity ofμ-LED and precisely monitoring the tumor size by Si phototransistor during a long-term implantation(2–3 weeks).The superiority of simultaneous cancer treatment and tumor size monitoring capabilities of our system operated by wireless power and data transmissions with a cell phone was confirmed through in vitro experiments,ray-tracing simulation results,and a tumor xenograft mouse model in *** all-in-one single system for cancer treatment offers opportunities to not only enable effective treatment of tumors located deep in the tissue but also enable precise and continuous monitoring of tumor size in real-time.

关键词： optoelectronic enable battery

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Study on the Plate Detection Method Based on the Data Generated by Significance Detection

Study on the Plate Detection Method Based on the Data Genera...

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Edge Computing and Scalable Cloud (EdgeCom), IEEE International Conference on

作者： Linzhong Fang Xuanlai Tang Shuyong Gao Yicheng Song Shengfeng Li School of Mechanical and Energy Engineering Shanghai Technical Institute of Electronics&Information Shanghai China KEENON Robotics Co. Ltd Shanghai China School of Computer Science Fudan University Shanghai China School of Communication and Information Engineering Shanghai Technical Institute of Electronics&Information Shanghai China

ISBN: (数字)9798350377132

ISBN: (纸本)9798350377149

In the smart restaurant environment, vision-based plate detection technology is the core of automated dish management. This study focuses on the identification of the existence of dishes on the plate, and constructs a data set of dishes on the plate by collecting data from the actual restaurant scene. In order to complete the detection of dinner plates, a plate detection model based on Yolov5 is designed. Due to the limitation of the available restaurant dishes, the data set has a single dish variety on the plate, which leads to the low performance of the trained plate detection model. In order to solve this problem, this paper proposes a plate data generation method based on salient object detection, which uses its category-independent characteristics to extract a variety of dish data from various scenarios, and completes the annotation of the generated data by designing prompts and combining with Grounding DINO, which effectively solves the problem of the scarcity of plate data and dish types. Experimental results show that the proposed plate detection model can effectively detect the presence of dishes on plates in a variety of restaurant environments, and the data generation method based on salient object detection significantly improves the quality of the data set and the performance of the plate detection model.

关键词： YOLO Training Annotations Grounding Pipelines Lighting Data models

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Fixed-time Adaptive Neural Control for Physical Human-Robot Collaboration with Time-Varying Workspace Constraints

arXiv

引用

arXiv 2023年

作者： Sun, Yuzhu Van, Mien McIlvanna, Stephen Nhat, Nguyen Minh McLoone, Seán Ceglarek, Dariusz Ge, Shuzhi Sam The Centre for Intelligent Autonomous Manufacturing Systems School of Electronics Electrical Engineering and Computer Science Queen’s University Northern Ireland Belfast United Kingdom The Warwick Manufacturing Group University of Warwick Coventry United Kingdom The Department of Electrical and Computer Engineering Social Robotics Laboratory National University of Singapore Singapore

Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a novel fixed-time adaptive neural control methodology for handling time-varying workspace constraints that occur in physical human-robot collaboration while also guaranteeing compliance during intended force interactions. The proposed methodology combines the benefits of compliance control, time-varying integral barrier Lyapunov function (TVIBLF) and fixed-time techniques, which not only achieve compliance during physical contact with human operators but also guarantee time-varying workspace constraints and fast tracking error convergence without any restriction on the initial conditions. Furthermore, a neural adaptive control law is designed to compensate for the unknown dynamics and disturbances of the robot manipulator such that the proposed control framework is overall fixed-time converged and capable of online learning without any prior knowledge of robot dynamics and disturbances. The proposed approach is finally validated on a simulated two-link robot manipulator. Simulation results show that the proposed controller is superior in the sense of both tracking error and convergence time compared with the existing barrier Lyapunov functions based controllers, while simultaneously guaranteeing compliance and safety. Copyright © 2023, The Authors. All rights reserved.

关键词： Lyapunov functions

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