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Optical Based Gradient-Weighted Class Activation Mapping and Transfer Learning Integrated Pneumonia Prediction Model

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Computer Systems Science & engineering 2023年第12期47卷 2989-3010页

作者： Chia-Wei Jan Yu-Jhih Chiu Kuan-Lin Chen Ting-Chun Yao Ping-Huan Kuo Department of Mechanical Engineering National Chung Cheng UniversityChiayi62102Taiwan Department of Intelligent Robotics National Pingtung UniversityPingtung900392Taiwan School of Medicine College of MedicineTaipei Medical UniversityTaipei CityTaiwan Advanced Institute of Manufacturing with High-Tech Innovations(AIM-HI) National Chung Cheng UniversityChiayi62102Taiwan

Pneumonia is a common lung disease that is more prone to affect the elderly and those with weaker respiratory ***,hospital medical resources are limited,and sometimes the workload of physicians is too high,which can affect their ***,a good medical assistance system is of great significance for improving the quality of medical *** study proposed an integrated system by combining transfer learning and gradient-weighted class activation mapping(Grad-CAM).Pneumonia is a common lung disease that is generally diagnosed using ***,in areaswith limited medical resources,a shortage of medical personnel may result in delayed diagnosis and treatment during the critical ***,overworked physicians may make diagnostic ***,having an X-ray pneumonia diagnosis assistance system is a significant tool for improving the quality of medical *** result indicates that the best results were obtained by a ResNet50 pretrained model combined with a fully connected classification layer.A retraining procedure was designed to improve accuracy by using gradient-weighted class activation mapping(Grad-CAM),which detects the misclassified images and adds weights to *** the evaluation tests,the final combined model is named Grad-CAM Based Pneumonia Network(GCPNet)out performed its counterparts in terms of accuracy,precision,and F1 score and reached 97.2%*** integrated system is proposed to increase model performance where Grad-CAM and transfer learning are ***-CAM is used to generate the heatmap,which shows the region that the model is focusing *** outcomes of this research can aid in diagnosing pneumonia symptoms,as themodel can accurately classify chest X-ray images,and the heatmap can assist doctors in observing the crucial areas.

关键词： Data augmentation deep neural network image classification medical imaging transfer learning Grad-CAM

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Quaternion-Based Attitude Stabilization Using Synergistic Hybrid Feedback With Minimal Potential Functions

arXiv

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arXiv 2024年

作者： Tong, Xin Ding, Qingpeng Fang, Haiyang Cheng, Shing Shin Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong Shun Hing Institute of Advanced Engineering The Chinese University of Hong Kong Hong Kong

This paper investigates the robust global attitude stabilization problem for a rigid-body system using quaternion-based feedback. We propose a novel synergistic hybrid feedback with the following notable features: (1) It demonstrates central synergism by utilizing a minimal number of potential functions;(2) It ensures consistency with respect to the unit quaternion representation of rigid-body attitude;(3) Its state-feedback laws incorporate a shared action term that steers the system toward the desired attitude. We demonstrate that the proposed hybrid feedback method effectively solves the problem at hand and guarantees robust uniform global asymptotic stability. © 2024, CC BY-NC-ND.

关键词： Attitude control

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Active-type piezoelectric smart textiles with antifouling performance for pathogenic control

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npj Flexible Electronics 2024年第1期8卷 223-232页

作者： Su Eon Lee Hanna Lee Jang Hwan Kim Jae Chul Park Sooah Kyung Hayoung Choi Su Hyun Baek Jun Hyun Park Sohyun Park Jeong-Min Kim Hye-Jun Jo Seung Hyeon Cho Jiwoong Kim Hojun Kim Seung Ho Han Jun Kyun Oh Bong Hoon Kim Department of Robotics and Mechatronics Engineering DGISTDaegu42988Republic of Korea Department of Polymer Science and Engineering Dankook UniversityYongin16890Republic of Korea Department of Materials Science and Engineering Ajou UniversitySuwon16499Republic of Korea Center for Advanced Biomolecular Recognition KISTSeoul02792Republic of Korea Department of Materials Science and Engineering Soongsil UniversitySeoul06978Republic of Korea Division of Emerging Infectious Diseases KDCACheongju28159Republic of Korea Safety Measurement Institute Korea Research Institute of Standards and Science(KRISS)Daejeon34113Republic of Korea Division of Bio-Medical Science and Technology KIST SchoolUST02792 SeoulRepublic of Korea Electronic Convergence Materials&Devices Research Center Korea Electronics Technology Institute(KETI)13509 SeongnamRepublic of Korea

Recently,an investigation into preventive measures for coronavirus disease 2019(COVID-19)has garnered considerable ***,strategies for the proactive prevention of viral pathogens have also attracted significant interest in the field of wearable devices and electronic textiles research,particularly due to their potential applications in personal protective *** this study,we introduce smart textiles designed with optimized piezoelectric devices that exhibit antifouling performance against microorganisms and actively inactivate *** active-type smart textiles,which incorporate advanced lead zirconate titanate(PZT)ceramics,a stretchable interconnector array,and polymeric fabric,demonstrate effective antifouling capabilities,detaching approximately90%of Escherichia coli and75%of ***,they inactivate viruses,releasing~26.8 ng of N protein from ruptured SARS-CoV-2,using ultrasonic waves within the wearable *** results show that piezoelectric smart textiles significantly reduce the spread of COVID-19 by leveraging the electrical and acoustic properties of PZT ceramics.

关键词： textiles smart piezoelectric

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Soft Cap for Eversion Robots

arXiv

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arXiv 2023年

作者： Suulker, Cem Skach, Sophie Kaleel, Danyaal Abrar, Taqi Murtaza, Zain Suulker, Dilara Althoefer, Kaspar Centre for Advanced Robotics @ Queen Mary School of Engineering and Materials Science School of Electronic Engineering and Computer Science United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom

Growing robots based on the eversion principle are known for their ability to extend rapidly, from within, along their longitudinal axis, and, in doing so, reach deep into hitherto inaccessible, remote spaces. Despite many advantages, eversion robots also present significant challenges, one of which is maintaining sensory payload at the tip without restricting the eversion process. A variety of tip mechanisms have been proposed by the robotics community, among them rounded caps of relatively complex construction that are not always compatible with functional hardware, such as sensors or navigation pouches, integrated with the main eversion structure. Moreover, many tip designs incorporate rigid materials, reducing the robot’s flexibility and consequent ability to navigate through narrow openings. Here, we address these shortcomings and propose a design to overcome them: a soft, entirely fabric based, cylindrical cap that can easily be slipped onto the tip of eversion robots. Having created a series of caps of different sizes and materials, an experimental study was conducted to evaluate our new design in terms of four key aspects: eversion robot made from multiple layers of everting material, solid objects protruding from the eversion robot, squeezability, and navigability. In all scenarios, we can show that our soft, flexible cap is robust in its ability to maintain its position and is capable of transporting payloads such as a camera across long distances. We also demonstrate that the robot’s ability to move through restricted aperture openings and indeed its overall flexibility is virtually unhindered by the addition of our cap. The paper discusses the advantages of this design and gives further recommendations in relation to aspects of its engineering. © 2023, CC BY.

关键词： Robots

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A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Robot System and Its Applications

A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Ro...

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International Conference on Mechatronics (ICM)

作者： Kitti Suwanratchatamanee Hideyuki Sawada Shuji Hashimoto Robotics Research and Development Center GOLDEN ROBOT Co. Ltd. Rayong Thailand Grad. School of Advanced Science and Engineering WASEDA University Tokyo Japan WASEDA University Tokyo Japan

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

Industrial robots are increasingly being used to assist and replace workers in factories to address the global labor shortage in various applications. The use of robots can provide many benefits to the effective production and manufacturing. Taping is one of the robots' applications. However, current tape robots can only tape one strip at a time, which can be time-consuming in practice if multiple strips of tape are required at the same time for special workpieces. This paper presents a novel sticking adhesive tape robot system. As the object to be taped are four-line hot pipes to be attached on the outer shell of refrigerator, thus four strips of tape are required at the same time before assembly process. The proposed robot system contains the novel tooling called “Quadruple Dispensing Heads”. This tooling was developed to tape four strips of tape to be applied simultaneously. This tooling can adjust the gap of tape strips from 80mm to 110mm. Moreover, the research objective is to produce a robot system that can apply tape with higher quality and faster than human workers, so that human workers can move on to more complicated tasks instead of performing repetitive, routine tasks that do not require such special skills and knowledge. As the result, our proposed system can achieve the four lines of *** length, through IS7N pushing force (when operate the air working pressure at ***) sticking taping task perfectly with 100% success rate of experiments in just 3 seconds and faster than human worker significantly. Since, human worker needs about 3 seconds per each I.5m taping line. Therefore, human needs approximately 12 seconds in total for four lines. Accordingly, our proposed robot system is faster than human worker in four times.

关键词： Strips Mechatronics Service robots Force Industrial robots Production facilities Robots Assembly

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A Cable-driven Robot for Indoor Acrylic Emulsion Painting

A Cable-driven Robot for Indoor Acrylic Emulsion Painting

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Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), International Conference on

作者： A Akarawarit S Vongbunyong Innovation and Advanced Manufacturing Research Group Institute of Field Robotics King Mongkut’s University of Technology Bangkok Thailand Vasin Engineering Corporation Bangkok Thailand

Nowadays, the construction industry has expanded but the number of labors tends to decrease. A number of safety regulations in accordance with chemical working performed by human workers are involved in construction work, especially painting process. The concept of developing a cable-driven robot for wall spraying with Acrylic watercolor for indoor construction are initiated. The operation of this robot is designed to be moveable and easy to install. The Robot module is linked with soft cables and control by stepper motors for controlling moving path of an industrial paint nozzle. In this research, the prototype is determined to work with at least 90% efficiency on 1.2m x 2.4m panels. However, the system still requires human labor to install the spray paint robot system and finish off the detailed correction nearby the border area where the nozzle cannot reach. This project is expected to be able to increase workplace safety standard and reduce the number of workers for this activity.

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Compliant Finger Joint with Controlled Variable Stiffness based on Twisted Strings Actuation

Compliant Finger Joint with Controlled Variable Stiffness ba...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Mihai Dragusanu Danilo Troisi Domenico Prattichizzo Monica Malvezzi Department of Information Engineering and Mathematics University of Siena Siena Italy Department of Information Engineering University of Pisa Pisa Italy Department of Advanced Robotics Istituto Italiano di Tecnologia Genova Italy

Underactuated tendon-driven fingers are a simple, yet effective solution, for realizing robotic grippers and hands. The lack of controllable degrees of actuation and precise sensing is compensated by the deformable structure of the finger, which is able to adapt to the objects to be grasped and manipulated, and also to implement grasping strategies based on environmental constraint exploitation. One of the main drawbacks of these robotic fingers is that, due to the limited number of actuators, they can only realize a limited number of movements. Finger closure motion realized by activating the tendon depends on finger mechanical properties, and in particular on elastic joint stiffness. In this paper, we introduce a passive elastic joint to be implemented in monolithic fingers in which the stiffness can be actively regulated by applying a pre-compression to the structure, controlled by a twisted-string actuator (TSA). The paper describes the working principle of the joint, investigates the relationship between pre-compression and flexural stiffness, and finally shows its application to a robotic finger composed of three phalanges.

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BRNES: Enabling Security and Privacy-aware Experience Sharing in Multiagent Robotic and Autonomous Systems

arXiv

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arXiv 2023年

作者： Hossain, Md Tamjid La, Hung Manh Badsha, Shahriar Netchaev, Anton The Advanced Robotics and Automation Lab Computer Science and Engineering University of Nevada RenoNV United States Bosch Engineering North America The U.S. Army Corps United States

Although experience sharing (ES) accelerates multiagent reinforcement learning (MARL) in an advisor-advisee framework, attempts to apply ES to decentralized multiagent systems have so far relied on trusted environments and overlooked the possibility of adversarial manipulation and inference. Nevertheless, in a real-world setting, some Byzantine attackers, disguised as advisors, may provide false advice to the advisee and catastrophically degrade the overall learning performance. Also, an inference attacker, disguised as an advisee, may conduct several queries to infer the advisors’ private information and make the entire ES process questionable in terms of privacy leakage. To address and tackle these issues, we propose a novel MARL framework (BRNES) that heuristically selects a dynamic neighbor zone for each advisee at each learning step and adopts a weighted experience aggregation technique to reduce Byzantine attack impact. Furthermore, to keep the agent’s private information safe from adversarial inference attacks, we leverage the local differential privacy (LDP)-induced noise during the ES process. Our experiments show that our framework outperforms the state-of-the-art in terms of the steps to goal, obtained reward, and time to goal metrics. Particularly, our evaluation shows that the proposed framework is 8.32x faster than the current non-private frameworks and 1.41x faster than the private frameworks in an adversarial setting. © 2023, CC BY-NC-SA.

关键词： Multi agent systems

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A Novel Multivariate Skew-Normal Mixture Model and Its Application in Path-Planning for Very-Large-Scale Robotic Systems

arXiv

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arXiv 2024年

作者： Zhu, Pingping Liu, Chang Estephan, Peter Faculty of Computer Sciences and Electrical Engineering Marshall University HuntingtonWV United States Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Department of Computer Sciences and Electrical Engineering Marshall University HuntingtonWV United States

This paper addresses the path-planning challenge for very large-scale robotic systems (VLSR) operating in complex and cluttered environments. VLSR systems consist of numerous cooperative agents or robots working together autonomously. Traditionally, many approaches for VLSR systems are developed based on Gaussian mixture models (GMMs), where the GMMs represent agents' evolving spatial distribution, serving as a macroscopic view of the system's state. However, our recent research into VLSR systems has unveiled limitations in using GMMs to represent agent distributions, especially in cluttered environments. To overcome these limitations, we propose a novel model called the skew-normal mixture model (SNMM) for representing agent distributions. Additionally, we present a parameter learning algorithm designed to estimate the SNMM's parameters using sample data. Furthermore, we develop two SNMM-based path-planning algorithms to guide VLSR systems through complex and cluttered environments. Our simulation results demonstrate the effectiveness and superiority of these algorithms compared to GMM-based pathplanning methods. © 2024, CC BY.

关键词： Motion planning

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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

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Computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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