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Thermal Hall effect in insulating quantum materials

The Innovation 2022年第5期3卷 3-4页

作者： Shucheng Guo Youming Xu Ran Cheng Jianshi Zhou Xi Chen Department of Electrical and Computer Engineering University of CaliforniaRiversideRiversideCA 92521USA Department of Physics and Astronomy University of CaliforniaRiversideRiversideCA 92521USA Materials Science and Engineering Program Department of Mechanical EngineeringUniversity of Texas at AustinAustinTX 78712USA

The emerging field of quantum materials involves an exciting new class of materials in which charge,spin,orbital,and lattice degrees of freedom are intertwined,exhibiting a plethora of exotic physical *** materials include,but are not limited to,superconductors,topological quantum matter,and systems with frustrated spins,which enable a wide range of potential applications in biomedicine,energy transport and conversion,quantum sensing,and quantum information processing。

关键词： properties. quantum topological

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Excavation pits—progress estimation and cause of delay identification

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Construction robotics 2023年第1期7卷 53-63页

作者： Vierling, Axel Groll, Tobias Meckel, Dennis Heim, Kristina Walter, Daniel Körkemeyer, Dr. Karsten Berns, Dr. Karsten Department of Computer Science Robotics Research Lab University of Kaiserslautern-Landau Kaiserslautern Germany Department of Civil Engineering Chair in Construction Management University of Kaiserslautern-Landau Kaiserslautern Germany

This work presents a method for automated excavation speed and progress estimation. First, a measure for the progress speed of an excavation pit is taken from the literature and evaluated regarding the possibility of automation. For each possible parameter, an automated extraction algorithm is presented. The used system is an autonomous excavator arm of a backhoe loader where the used hardware and software system is described. An experimental evaluation of the presented approach has been done with the autonomous system for a small trench, including multiple digging cycles. The resulting measurements seem to include some systematic errors which could be identified and suitable sanity checks could be implemented, removing the erroneous measurements. The remaining measurements were used to determine the excavation speed of the autonomous excavator arm and compared to the values of experienced and amateur operators. The resulting speed and the relevant parameters are then sent to a web application called “DiBa” to notice a potential delay. If a measurement is smaller or larger than expected a fault identification is done in the DiBa.

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WildGaussians: 3D Gaussian splatting in the wild 24

WildGaussians: 3D Gaussian splatting in the wild

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Jonas Kulhanek Songyou Peng Zuzana Kukelova Marc Pollefeys Torsten Sattler Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague and Faculty of Electrical Engineering Czech Technical University in Prague and Department of Computer Science ETH Zurich Department of Computer Science ETH Zurich Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague

ISBN: (纸本)9798331314385

While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods primarily excel with well-controlled 3D scenes, while in-the-wild data - characterized by occlusions, dynamic objects, and varying illumination - remains challenging. NeRFs can adapt to such conditions easily through per-image embedding vectors, but 3DGS struggles due to its explicit representation and lack of shared parameters. To address this, we introduce WildGaussians, a novel approach to handle occlusions and appearance changes with 3DGS. By leveraging robust DINO features and integrating an appearance modeling module within 3DGS, our method achieves state-of-the-art results. We demonstrate that WildGaussians matches the real-time rendering speed of 3DGS while surpassing both 3DGS and NeRF baselines in handling in-the-wild data, all within a simple architectural framework.

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Imaging atomic-scale chemistry from fused multi-modal electron microscopy

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npj Computational Materials 2022年第1期8卷 164-171页

作者： Jonathan Schwartz Zichao Wendy Di Yi Jiang Alyssa J.Fielitz Don-Hyung Ha Sanjaya D.Perera Ismail El Baggari Richard D.Robinson Jeffrey A.Fessler Colin Ophus Steve Rozeveld Robert Hovden Department of Materials Science and Engineering University of MichiganAnn ArborMIUSA Mathematics and Computer Science Division Argonne National LaboratoryLemontILUSA Advanced Photon Source Facility Argonne National LaboratoryLemontILUSA Dow Chemical Co. MidlandMIUSA Department of Material Science and Engineering Cornell UniversityIthacaNew YorkUSA School of Integrative Engineering Chung-Ang UniversitySeoulRepublic of Korea Department of Physics Cornell UniversityIthacaNYUSA The Rowland Institute at Harvard CambridgeMAUSA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMIUSA National Center for Electron Microscopy Lawrence Berkeley National LaboratoryMolecular FoundryBerkeleyCAUSA Applied Physics Program University of MIchiganAnn ArborMIUnited States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic ***,fused multi-modal electron microscopy offers high signal-to-noise ratio(SNR)recovery of material chemistry at nano-and atomic-resolution by coupling correlated information encoded within both elastic scattering(high-angle annular dark-field(HAADF))and inelastic spectroscopic signals(electron energy loss(EELS)or energy-dispersive x-ray(EDX)).By linking these simultaneously acquired signals,or modalities,the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector *** many cases,the dose requirements can be reduced by over one order of *** high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

关键词： materials chemistry fused

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Toward Closed-Loop Additive Manufacturing: Paradigm Shift in Fabrication, Inspection, and Repair

Toward Closed-Loop Additive Manufacturing: Paradigm Shift in...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Manpreet Singh Fujun Ruan Albert Xu Yuchen Wu Archit Rungta Luyuan Wang Kevin Song Howie Choset Lu Li Department of Mechanical Engineering Carnegie Mellon University Pittsburgh USA CMU The Robotics Institute School of Computer Science USA Department of Electrical Engineering and Computer Science University of Michigan USA Department of Electrical and Electronics Engineering Birla Institute of Technology and Science Pilani India Department of Electrical and Computer Engineering CMU USA

Increased usage of additive manufacturing (AM) in various industries has solidified its role as an advanced manufacturing technique. However, there is an inherent lack of reliability in AM processes, particularly common in extrusion or deposition-based methods due to the stochastic nature of ma-terial deposition. This necessitates an intelligent manufacturing solution to address the drawbacks of AM. Thus, we propose a novel layer-wise approach toward closed-loop AM, which is capable of in-situ monitoring and repairing geometric defects. In this paper, we present a system that uses a robotic AM experimental platform that mimics a conventional open-loop fabrication setup, which we augment into a closed-loop system using two add-ons: in-situ inspection subsystem and online process correction subsystem. The in-situ inspection subsystem collects 3D point cloud scans and compares them against a reference CAD model, categorizing geometric deviations as positive or negative defects. Then the subsequent online process correction subsystem uses a re-plan and/or repair strategy to address the positive and/or negative defects, respectively. To evaluate this idea, we conducted three experiments on parts with manually induced defects to investigate the system's ability to repair those parts, thereby reducing defects, improving part accuracy, and enhancing mechanical properties. Comparing the defective and repaired parts, we observe a reduction in defect percent by volume from 10.7% to 1.3%, an improvement in geometric tolerance from 3.86% error to 0.08% error, and an increase in the part's breaking load from 4.77 kN to 6.31 kN. These experiments prove that our layer-wise closed-loop additive manufacturing approach improves the quality, tolerance, and reliability of plastic 3D printed parts, with the potential to extend to other extrusion/deposition-based AM processes, or even subtractive manufacturing and hybrid manufacturing methods.

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An Perception Enhanced Human-Robot Skill Transfer Method for Reactive Interaction 25th

An Perception Enhanced Human-Robot Skill Transfer Method for...

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25th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2024

作者： Si, Weiyong Dong, Jiale Wang, Ning Yang, Chenguang School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park ColchesterCO4 3SQ United Kingdom South China University of Technology Guangzhou510640 China Bristol Robotics Lab University of the West of England BristolBS16 1QY United Kingdom Department of Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom

ISBN: (纸本)9783031720611

In this paper, we propose a trust human-robot skill transfer framework, interpretive and reactive dynamic system (IRDS), by investigating the behaviour tree (BT) and dynamic movement primitives (DMPs) enhanced by the feedback from perceived information for dynamic and uncertain tasks and environments. Human sensorimotor control allows interactions with various environments and accomplishes complex manipulation tasks with uncertainty;however, it is still hard for robots to own this capability. In this work, we aim to transfer these reactive skills to robots, which enable robots to interact with humans and environments under varying uncertainty. The main challenges of robot skill learning are the generalization, safety and stability issues during the skills learning and execution autonomously. BT was investigated for task planning and reactive interaction during the robot execution. The dynamic system-based model generates action for the low-level compliant controller. The convergence of the proposed IRDS framework under dynamic interaction and disturbance was proved by control theory. We conducted simulations and physical experiments on the real robots to evaluate the generalization performance and the convergence capability under uncertainty. And the results show that the reactivity, convergence and interaction performance can be guaranteed, and the learned skills can be transferred among different physical robot platforms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Human robot interaction

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IBURD: Image Blending for Underwater Robotic Detection

arXiv

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arXiv 2025年

作者： Hong, Jungseok Singh, Sakshi Sattar, Junaed Department of Computer Science and Engineering Minnesota Robotics Institute University of Minnesota–Twin Cities 100 Union St SE MinneapolisMN55455 United States

We present an image blending pipeline, IBURD, that creates realistic synthetic images to assist in the training of deep detectors for use on underwater autonomous vehicles (AUVs) for marine debris detection tasks. Specifically, IBURD generates both images of underwater debris and their pixel-level annotations, using source images of debris objects, their annotations, and target background images of marine environments. With Poisson editing and style transfer techniques, IBURD is even able to robustly blend transparent objects into arbitrary backgrounds and automatically adjust the style of blended images using the blurriness metric of target background images. These generated images of marine debris in actual underwater backgrounds address the data scarcity and data variety problems faced by deep-learned vision algorithms in challenging underwater conditions, and can enable the use of AUVs for environmental cleanup missions. Both quantitative and robotic evaluations of IBURD demonstrate the efficacy of the proposed approach for robotic detection of marine debris. Copyright © 2025, The Authors. All rights reserved.

关键词： Image annotation

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The ways in which Artificial Intelligence improves several facets of Cyber Security-A survey 1

The ways in which Artificial Intelligence improves several f...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Altrjman, Chadi Bordoloi, Dibyahash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Waterloo University Canada Graphic Era Hill University Dehradun Rs Cse Graphuc Era University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350338027

With the increase in computer use for the last 10 years, it increases the size of cyber-attacks as well. Since most computers are connected to the network, they may suffer cyber-attacks. Because of these cyber threats, Cyber Security is becoming a really important area in the information technology area. Cyber Security is an area which is mainly responsible for dealing with cyber-attacks by hackers. The improvements and advancements in the information technology area allow cyber criminals to do really complicated and dangerous cyber-attacks. Cyber-attack methods that are being used today are much more effective than the ones in the past. Because of that, there is always a war between cyber security specialists and cyber attackers or hackers. Cyber security analysts, on the other hand, try to come up with new solutions to the methods developed by cyber criminals or hackers. The competition between them continuously advances and improves cyber security technologies every day. The improvements can be either in cyber security or cybercrime side. These days, traditional cyber security solutions are enough to fight against cyber-attacks, but can these solutions be further developed? This is the question everyone in the cyber security area is trying to answer. Of course, yes. Thanks to AI, which is one of the most popular technologies in the information technology area, it is used in many areas ranging from e-commerce, advertising, human resource & recruiting, video games, transportation, surveillance systems etc. AI has been used in cyber security over the last years. Although it also has negative effects, we are going to mostly talk about its positive sides in this article. We are going to go deep into how and why AI is used in cyber security, how AI improves and enhances the current traditional cyber security methods. Then, we will also talk about which AI techniques play an important role in the cyber security area. © 2023 IEEE.

关键词： Artificial intelligence

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CredChain: Academic and Professional Certificate Verification System using Blockchain

CredChain: Academic and Professional Certificate Verificatio...

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Advances in Computing,Communication, Electrical, and Smart Systems (iCACCESS), International Conference on

作者： Saniyat Al Ahmed Rifat Al Mamun Rudro Afrina Jannat Prity Suman Saha Nafees Mansoor Kamruddin Nur Department of Computer Science American International University-Bangladesh (AIUB) Dhaka Bangladesh Department of IoT and Robotics Engineering Bangabandhu Sheikh Mujibur Rahman Digital University Bangladesh Gazipur Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh (ULAB) Dhaka Bangladesh

The integrity of academic and professional creden-tials is a foundation in education and the professional fields. Traditional certificate verification methods are flawed by in-efficiencies, susceptibility to fraud, and a reliance on manual processes that compromise security and expedience. To address these issues, we present CredChain, a robust Academic and Professional Certificate Verification System that harnesses the power of blockchain technology. Our system utilizes Ethereum-based Decentralized Applications (DApps) and Smart Contracts integrated with the InterPlanetary File System (IPFS) to ensure immutable, secure, and transparent verification processes. We outline the novel algorithms for essential system functions such as certificate uploading, verification, and retrieval of certificates. The CredChain system has been subjected to rigorous testing and validation, demonstrating its effectiveness in mitigating the risk of fraudulent certificates and streamlining the verification process accurately.

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Development of Support Vector Machine Method to Forecast Dengue-Endemic Areas

Development of Support Vector Machine Method to Forecast Den...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Meileni, Hetty Ermatita Abdiansah Husni, Nyayu Latifah Desmawati Doctoral Program in Engineering Science Palembang30139 Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang30139 Indonesia Palembang30139 Indonesia Politeknik Negeri Sriwijaya Palembang Department of Electrical Engineering Palembang30139 Indonesia Universitas Pembangunan Nasional Veteran Jakarta Faculty of Health Science Jakarta12450 Indonesia

ISBN: (纸本)9798350307306

The cases of dengue hemorrhagic fever (DHF) in Indonesia have increased significantly since 2020. Data shown by the Central Statistics Agency, for example, in South Sumatra Province, there were 6,348 cases of DHF during that period. To suppress the case number of DHF, forecasting areas that are susceptible to this disease is urgently needed. This research aims to develop a machine learning method Support Vector Machine (SVM). The data used include area data, population density data, weather data, and dengue fever case data. The development of the SVM model is carried out using a machine learning method that combines regional data, population density data, weather data, and dengue case data. In the end, using the SVM method can be used to forecast dengue-endemic areas, so that the government and society can take further action to reduce the negative impact of DHF. © 2023 IEEE.

关键词： Forecasting

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