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Recent advances in characterizing the "bee" structures and asphaltene particles in asphalt binders

International Journal of Pavement Research and Technology 2020年第6期13卷 697-706页

作者： Wang, Yuhong Zhao, Kecheng Li, Fangjin Gao, Qi Lai, King Wai Chiu Dept. of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong Zhejiang Communications Construction Group Co. Ltd. HangzhouZhejiang Province China Dept. of Biomedical Engineering Centre for Robotics and Automation City University of Hong Kong Hong Kong

The microscopic surface features of asphalt binders are extensively reported in existing literature, but relatively fewer studies are performed on the morphology of asphaltene microstructures and cross-examination between the surface features and asphaltenes. This paper reports the findings of investigating six types of asphalt binders at the nanoscale, assisted with atomic force microscopy (AFM) and scanning transmission electron microscopy (STEM). The surface features of the asphalt binders were examined by using AFM before and after being repetitively peeled by a tape. Variations in infrared (IR) absorbance at the wavenumber around 1700 cm−1, which corresponds to ketones, were examined by using an infrared s-SNOM instrument (scattering-type scanning near-field optical microscope). Thin films of asphalt binders were examined by using STEM, and separate asphaltene particles were cross-examined by using both STEM and AFM. In addition, connections between the microstructures and binder’s physicochemical properties were evaluated. The use of both microscopy techniques provide comprehensive and complementary information on the microscopic nature of asphalt binders. It was found that the dynamic viscosities of asphalt binders are predominantly determined by the zero shear viscosity of the corresponding maltenes and asphaltene content. Limited samples also suggest that the unique bee structures are likely related to the growth of asphaltene content during asphalt binder aging process, but more asphalt binders from different crude sources are needed to verify this finding. © 2020, The Author(s).

关键词： Microstructure

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A Novel Interoperability Evaluation Framework for the Warehouse Management System

A Novel Interoperability Evaluation Framework for the Wareho...

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Annual Conference of Industrial Electronics Society

作者： Tijo Thayil Jingbing Zhang Prahlad Vadakkepat Abdullah Al Mamun Krishna Sagar Smart Robotics and Automation Advanced Remanufacturing & Technology Centre (ARTC) Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore Dept. of Electrical and Computer Engineering College of Design and Engineering National University of Singapore Advanced Remanufacturing & Technology Centre (ARTC) Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore

Warehouse management is a critical element in the supply chain. The rise of e-commerce demands ‘any-mix any-volume’ customized and personalized orders. Due to the variety of products in ‘any-mix any-volume’ scenario the warehouse operations have become complex. The advent of multi-channel commerce has reduced the minimum order quantity (MOQ), claiming frequent changes. The ‘any-mix any-volume’ operations require flexible automation for product storage, retrieval, packing and shipping. Seamless operations of multiple devices are essential for automating flexible warehouses. For effective flexible operations, the Warehouse Management System (WMS) requires controlling the automation devices and associated auxiliary systems. Heterogenous automation devices with distinct communication protocols, data formats and connectivity are challenges for WMS centered control. An interoperable WMS can enable seamless communication and data exchange among devices. In this work, the interoperability of the WMS and various aspects of interoperability of engineering systems are presented. Different WMS system designs are considered and evaluated for the interoperability requirements. A framework for evaluating the interoperability of a WMS is proposed which is validated through experimental trials at an industry grade warehouse.

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Solution for Agri Disaster Using Climate Changes Adaptation by Ml

Solution for Agri Disaster Using Climate Changes Adaptation ...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： L. Ganesh R. Prasanna Venkatesh Kaushal Kumar Khushboo Kumari Sangeeta Borkakoty A. Raju Robotics and Automation Dept. Rajalakshmi Engineering College Chennai Tamilnadu India Department of Mechanical Engineering SACS MAVMM Engineering College Madurai Tamilnadu India Department of Botany School of Life Sciences Mahatma Gandhi Central University Bihar India Department of Computer Science & Electronic University of Science & Technology Meghalaya Department of Commerce KLEF Vaddeswaram Green Field Vijayawada

This paper proposes using good sized getting to know fashions to recognize lesions of cotton leaves in the context of pictures of the reaping within the subject. Cotton is among the maximum economically essential plant harvests, as it's far grown all over the international. Its spread in tropical areas has made it the goal of a wide variety of farming irritations and illnesses, necessitating succesful plans. moreover, the consequences of commonplace disturbances and disorders are difficult to isolate inside the early stages, and the author may additionally battle to locate the suitable visible verification of a scientific difficulty. To help in resolving the difficulty, it contemporary inquiry proposes a solution that takes into consideration substantial training within the filtering of cotton leaves, making it possible to reveal the cotton yield's health and make higher judgments approximately its management. The studying models GoogleNet like Resnet50, which use convolutional cerebrum associations, performed an accuracy of 86.6 percentage and 89.2 percentage, respectively. assist vector machines, Closest k-pals, faux creativeness associations, and neuro-tender are some of the extraordinary as well as everyday tactics again for treatment of photographs. The convolutional cerebellum networks ended up being 25% extra unique, implying that this method can upload to a more strong and short investigation of the flora looking to fill inside the field.

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Analysis of planar multilink cable driven robots using internal routing scheme

Analysis of planar multilink cable driven robots using inter...

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ASME 2020 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Ramadoss, Vishal Lau, Darwin Zlatanov, Dimiter Zoppi, Matteo PMAR Robotics University of Genoa Genoa16145 Italy Dept. of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9780791883990

The multilink cable driven robot (MCDR) is an extension of the cable robots where the moving platform is replaced by a multibody chain. It is typically an open-chain structure with multiple links and complex cable routing. This design introduces the advantages of having a serial kinematic structure and preserves the benefits associated with cable-driven parallel mechanism. To achieve a minimum number of actuating cables while possessing a large workspace region, a novel internal cable routing scheme is proposed. It is shown that by incorporating internal routing with multi-segment cables, any serial chain with n degrees of freedom can be controlled with n + 1 cables. In this work, through studying the kinematics and statics, we demonstrate how internally-routed cable actuation of multilink manipulators have an increased workspace and reduced cable forces to execute trajectories. Copyright © 2020 ASME

关键词： Cables

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Semiconductor Manufacturing Industry: Assessment, Challenges, and Future Trends

Semiconductor Manufacturing Industry: Assessment, Challenges...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Yasmin Musa Khalid Tantawi Maged Mikhail Jeffrey Ma Dalal Alharthi Larry Flatt Lyn Potter Department of Career Readiness Motlow State Community College Smyrna TN Department of Engineering Management and Technology University of Tennessee at Chattanooga TN Department of Engineering Technology Purdue University Northwest Hammond IN Department of Mechanical Engineering Saint Louis University Saint Louis MO College of Applied Science and Technology University of Arizona Tuscan AZ Director of the Robotics and Automation Center Motlow State Community College McMinnville TN Dept. of Engineering Systems Tech. Chattanooga State Community College Chattanooga State Community College Chattanooga TN

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

In this work we evaluate the state of the semiconductor manufacturing industry and its challenges and trends. Future trends in the industry are analyzed from three perspectives: the evolution of Industry 4.0, the advances in semiconductor materials, and the impact of the Covid-19 Pandemic. The semiconductor manufacturing industry witnessed an acute decline in the United States and other regions in the two decades prior to the CoVid-19 pandemic. The decline was only uncovered after the chip shortage of 2021 that resulted from the severe supply chain disruption. Trends in the industry were analyzed from three perspectives: Industry 4.0, advances in materials, and the Post-pandemic era. As a result of the evolution of the fourth generation of industry (Industry 4.0), trends in semiconductor manufacturing include robotization, which caused the industry to become the largest market for industrial robotics since 2020, and an all-time peak globalization. The semiconductor industry is a very globalized industry with corporates from different parts of the world taking part in the production of the final product. Although some materials such as carbon and Gallium Nitride show promising trends to replace silicon as the material of choice. It will likely not be before two or three decades when a semiconductor material will be able to replace silicon. Challenges for the industry include the shortage of the trained-workforce, and the added inter-country restrictions that may hinder the globalization of the industry.

关键词： Industries COVID-19 Pandemics Service robots Supply chains Globalization Semiconductor device manufacture Market research Silicon Fourth Industrial Revolution

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EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training

arXiv

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arXiv 2025年

作者： Tian, Qingyao Liao, Huai Huang, Xinyan Yang, Bingyu Lei, Dongdong Ourselin, Sebastien Liu, Hongbin State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Dept. of Radiology The First Affiliated Hospital Sun Yat-sen University Guangzhou China Centre for Artificial Intelligence and Robotics Chinese Academy of Sciences Hong Kong School of Engineering and Imaging Sciences King’s College London United Kingdom

Endoscopic video-based tasks, such as visual navigation and surgical phase recognition, play a crucial role in minimally invasive surgeries by providing real-time assistance. While recent video foundation models have shown promise, their applications are hindered by (1) computational inefficiencies and (2) suboptimal performance caused by limited data for pre-training in endoscopy. To address these issues, we present EndoMamba, a foundation model designed for real-time inference while learning generalized spatiotemporal representations. First, to mitigate computational inefficiencies, we propose the EndoMamba backbone, optimized for real-time inference. Inspired by recent advancements in state space models, EndoMamba integrates Bidirectional Mamba blocks for spatial modeling within individual frames and vanilla Mamba blocks for past-to-present reasoning across the temporal domain. This design enables both strong spatiotemporal modeling and efficient inference in online video streams. Second, we propose a self-supervised hierarchical pre-training diagram to enhance EndoMamba’s representation learning using endoscopic videos and incorporating general video domain knowledge. Specifically, our approach combines masked reconstruction with auxiliary supervision, leveraging low-level reconstruction to capture spatial-temporal structures and high-level alignment to transfer broader knowledge from a pretrained general-video domain foundation model. Extensive experiments on four downstream tasks—classification, segmentation, surgical phase recognition, and localization—demonstrate that EndoMamba outperforms existing foundation models and task-specific methods while maintaining real-time inference speed. The source code will be released upon acceptance. Copyright © 2025, The Authors. All rights reserved.

关键词： Endoscopy

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A surgical dataset from the da Vinci Research Kit for task automation and recognition

arXiv

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arXiv 2021年

作者： Mariani, Andrea Rivas-Blanco, Irene Pérez-Del-Pulgar, Carlos J. Tortora, Giuseppe Reina, Antonio J. Dept. Systems Engineering and Automation University of Malaga Malaga Spain The BioRobotics Institute Dept. Excellence in Robotics & AI Scuola Superiore Sant’Anna Pisa Italy Smart Medical Theatre Lab ABzero srl Pisa Italy

The use of large datasets is essential in surgical robotics to advance in the field of recognition and automation of surgical tasks. Furthermore, public datasets allow the comparison of different algorithms and methods to evaluate their performance. The objective of this work is to provide a complete dataset of three common training surgical tasks performed with the da Vinci Research Kit (dVRK). The dataset contains a total of 206 trials performed by twelve different subjects. For each trial, the dataset includes 154 kinematic variables from the dVRK (both master and slave sides) together with the associated video recorded with a camera. All the data has been carefully timestamped and provided in a readable csv format. A MATLAB interface integrated with ROS for using and replicating the data is also provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Large dataset

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ROBOSTEAMSEN Project - Training SEN Teachers to Use robotics for Fostering STEAM and Develop Computational Thinking*

ROBOSTEAMSEN Project - Training SEN Teachers to Use Robotics...

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International Symposium on Computers in Education (SIIE)

作者： Miguel Á. Conde Francisco J. Rodríguez-Sedano Francisco J. García-Peñalvo Jose Gonçalves Ilkka Jormanainen Andrea Anzanello Jonny Filipe Ribeiro Alves Raquel Fernández Hernáandez Alina- Andreia Ailincai Dept. of Mechanics Computer Science and Aerospace Engineering Universidad de Leon Leon Spain Dept. Electrical Systems and Automation Engineering Universidad de Leon Leon Spain Dpto. de Informatica y Autormatica - IUCE Universidad de Salamanca Salamanca Espana Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politecnico de Braganca Braganca Portugal School of Computing University of Eastern Finland Joensuu Finland Dept of Project Management Pixel Florence Italy Colegio Internato Dos Carvalhos Carvalhos Portugal Colegio de Educacion Especial Ntra. Sra. del Sagrado Corazon de Leon Leon Spain EuroEd Primary School Lasi Romania

ISBN: (数字)9798350376616

ISBN: (纸本)9798350376623

Our contemporary society necessitates professionals equipped with 21st-century skills. Disciplines within Science, Technology, engineering, Arts, and Mathematics (known as STEAM) have been particularly effective in fostering these skills. However, when considering students with disabilities, especially those with intellectual or developmental disabilities (IDD), this assertion often falls short. In this context, the RoboSTEAMSEN project emerges as an initiative designed to enhance educational processes by providing teachers of IDD students with the necessary resources to promote STEAM engagement. The project proposes the use of active learning methodologies and robotics to achieve this goal. The primary objective of the project is realized through several strategies: understanding the needs of students with disabilities and adapting the use of robotics and active learning methodologies accordingly; training teachers in the use of these resources; and creating a platform to exchange experiences, resources, lessons learned, tools, case scenarios, etc., while reaching other potential stakeholders such as caregivers and policymakers. The main outcomes of the project are teacher training programs and the development of associated competencies, tools to identify and classify resources for the students, and technological platforms to ensure the sustain ability of the project once it concludes.

关键词： Training Computers Ecosystems Collaboration Fasteners People with disabilities Mathematics

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A novel DMP formulation for global and frame independent spatial scaling in the task space

A novel DMP formulation for global and frame independent spa...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Leonidas Koutras Zoe Doulgeri Automation & Robotics Lab Dept. of Electrical & Computer Engineering Aristotle University of Thessaloniki Greece

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

In this work we study the DMP spatial scaling in the Cartesian space. The DMP framework is claimed to have the ability to generalize learnt trajectories to new initial and goal positions, maintaining the desired kinematic pattern. However we show that the existing formulations present problems in trajectory spatial scaling when used in the Cartesian space for a wide variety of tasks and examine their cause. We then propose a novel formulation alleviating these problems. Trajectory generalization analysis, is performed by deriving the trajectory tracking dynamics. The proposed formulation is compared with the existing ones through simulations and experiments on a KUKA LWR 4+ robot.

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Keep off the grass: Permissible driving routes from radar with weak audio supervision

arXiv

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arXiv 2020年

作者： Williams, David Martini, Daniele De Gadd, Matthew Marchegiani, Letizia Newman, Paul Oxford Robotics Institute Dept. Engineering Science University of Oxford Automation and Control Dept. Electronic Systems Aalborg University

Reliable outdoor deployment of mobile robots requires the robust identification of permissible driving routes in a given environment. The performance of LiDAR and vision-based perception systems deteriorates significantly if certain environmental factors are present e.g. rain, fog, darkness. Perception systems based on Frequency-Modulated Continuous Wave scanning radar maintain full performance regardless of environmental conditions and with a longer range than alternative sensors. Learning to segment a radar scan based on driveability in a fully supervised manner is not feasible as labelling each radar scan on a bin-by-bin basis is both difficult and time-consuming to do by hand. We therefore weakly supervise the training of the radarbased classifier through an audio-based classifier that is able to predict the terrain type underneath the robot. By combining odometry, GPS and the terrain labels from the audio classifier, we are able to construct a terrain labelled trajectory of the robot in the environment which is then used to label the radar scans. Using a curriculum learning procedure, we then train a radar segmentation network to generalise beyond the initial labelling and to detect all permissible driving routes in the environment. Copyright © 2020, The Authors. All rights reserved.

关键词： Landforms

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