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Magnetoelastic coupling driven magnon gap in a honeycomb antiferromagnet

Physical Review B 2024年第10期110卷 104419页

作者： Jeongheon Choe Andrey Baydin Gaihua Ye Bowen Ma Cynthia Nnokwe Martin Rodriguez-Vega David Lujan Swati Chaudhary Fuyang Tay Jiaming He Hiroyuki Nojiri Jianshi Zhou Gregory A. Fiete Junichiro Kono Rui He Xiaoqin Li Department of Physics Center of Complex Quantum Systems Center for Dynamics and Control of Materials Department of Electrical and Computer Engineering Smalley–Curl Institute Department of Physics Applied Physics Graduate Program Smalley–Curl Institute Department of Mechanical Engineering Institute for Materials Research Department of Physics and Astronomy Department of Materials Science and NanoEngineering

Cobalt titanate, CoTiO3, is a honeycomb antiferromagnet recently confirmed experimentally to host Dirac magnons, topological spin-orbit excitons, and chiral phonons. Here, we investigate a magnon gap at the zone center which calls for a refined spin Hamiltonian. We propose a microscopic model for the magnon gap and attribute it to a lattice-distortion (phonon)-induced higher-order spin interaction. Strong magnetoelastic coupling in CoTiO3 is also evident in Raman spectra, in which the magnetic order exerts a stronger influence on phonons corresponding to in-plane ionic motions than those with out-of-plane motions. We further examine the evolution of the zone-center magnons in a high magnetic field up to 18.5 T via THz absorption spectroscopy measurements. Based on this field dependence, we propose a spin Hamiltonian that not only agrees with magnon dispersion measured by inelastic neutron scattering but also includes fewer exchange constants and a realistic anisotropy term. Our work highlights the broad implications of magnetoelastic coupling in the study of topologically protected bosonic excitations.

关键词： Magnetism Magnons Topological materials Raman spectroscopy Terahertz spectroscopy

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An Improvement of Three-Factor Remote User Authentication Protocol Using ECC

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International Journal of Network Security 2024年第3期26卷 528-534页

作者： Hwang, Min-Shiang Lin, Cheng-Ying Wu, Chia-Chun Department of Computer Science & Information Engineering Asia University Taichung Taiwan 500 Lioufeng Rd. Wufeng Taichung Taichung 41354 Taiwan Department of Medical Research China Medical University Hospital China Medical University Taiwan Ph.D. Program in Artificial Intelligence Asia University Taichung Taiwan 500 Lioufeng Rd. Wufeng Taichung Taichung 41354 Taiwan Kinmen892 Taiwan

With the development of the Internet, many patients’ private medical data are maliciously stolen by attackers. Therefore, Liu et al. proposed an improved ECC-based three-factor user authentication scheme. The main advantage of their scheme is that it provides the same or better security than other schemes using more secondary keys. However, this article will show that Liu et al.’s scheme is vulnerable to denial of service attacks. In addition, their protocol uses public key cryptography, which is inefficient. Finally, the method is not immune to counterfeit smart card attacks. In this paper, we also improve their protocol from the perspective of practicality and security. © (2024), (International Journal of Network Security). All rights reserved.

关键词： Authentication

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Extinguishing Real Fires by Fully Autonomous Multirotor UAVs in the MBZIRC 2020 Competition

Field Robotics

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Field robotics 2025年 2卷 406-436页

作者： Viktor Walter Vojtěch Spurný Matěj Petrlík Tomáš Báča David Žaitlík Lyubomyr Demkiv Martin Saska Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague http://mrs.felk.cvut.cz Robotics Group of SoftServe Inc. and with the Institute of Computer Science and Information Technologies Lviv Polytechnic National University Ukraine

In this paper, we describe a system for combating real fires with sprayed liquid extinguishing agent using a team of multirotor UAVs. The system design relies on onboard sensors and operates without the need for human intervention throughout its complex mission, from its takeoff to landing. The core UAV platform can estimate its state, self-localize, navigate and locate and extinguishing fires. Thermal and RGB cameras are used, each with a specialized computer vision subsystem and are combined with planar LIDAR for 3D localization of fires on multistory building facades. The system conducts aerial firefighting with a software stack that addresses flight dynamics and sensor limitations and a liquid-spraying subsystem incorporating a rigidly-attached water nozzle. The approach presented in this paper was motivated by the Mohamed Bin Zayed International robotics Challenge (MBZIRC 2020) firefighting scenario, which focused on coordinated multi-UAV teams that can autonomously combat high-rise building fires. The MBZIRC series places particular emphasis on fast and reliable deployment of robots in realistic conditions. These contests promote development of real-world applications that are greatly needed by society, but which still exceed State-of-the-Art in the robotics community. To our knowledge, our system was the only MBZIRC 2020 contender to extinguish a facade fire successfully in autonomous mode without using an RTK-GNSS system. Our approach contributed to victory in the overall competition and we have now adapted it into an industrial prototype for a firefighting UAV. A video attachment to this paper is available at http://***/fr2020firechallenge-facadefires.

关键词： Robots Buildings Autonomous aerial vehicles Location awareness Robot kinematics Inspection Navigation Cameras Monitoring Sensor systems

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ODD: Omni Differential Drive for Simultaneous Reconfiguration and Omnidirectional Mobility of Wheeled Robots

arXiv

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arXiv 2024年

作者： Zhao, Ziqi Xie, Peijia Meng, Max Q.-H. Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong The Department of Electrical and Computer Engineering The University of Alberta Canada

Wheeled robots are highly efficient in human living environments. However, conventional wheeled designs, with their limited degrees of freedom and constraints in robot configuration, struggle to simultaneously achieve stability, passability, and agility due to varying footprint needs. This paper proposes a novel robot drive model inspired by human movements, termed as the Omni Differential Drive (ODD). The ODD model innovatively utilizes a lateral differential drive to adjust wheel spacing without adding additional actuators to the existing omnidirectional drive. This approach enables wheeled robots to achieve both simultaneous reconfiguration and omnidirectional mobility. To validate the feasibility of the ODD model, a functional prototype was developed, followed by comprehensive kinematic analyses. Control systems for self-balancing and motion control were designed and implemented. Experimental validations confirmed the feasibility of the ODD mechanism and the effectiveness of the control strategies. The results underline the potential of this innovative drive system to enhance the mobility and adaptability of robotic platforms. Copyright © 2024, The Authors. All rights reserved.

关键词： Kinematics

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Initial Study of Oil Palm Crop Condition Detection Through Drone Imagery: A YOLO Approach

Initial Study of Oil Palm Crop Condition Detection Through D...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Winata Nugraha Ermatita Deris Stiawan Faculty of Computer Science Doctoral Program Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Department of Information System Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Oil palm plantations in Indonesia still have many challenges, especially in terms of monitoring and mapping technology. One of the important aspects in the monitoring stage of oil palm plantations is monitoring the productivity of oil palm plants. To identify the oil palm plants, many previous studies have utilized image analysis to solve the problem. The problem is that poor image conditions can affect the architecture model to be built.[1] So in this research we do tune mapping on the image to produce a quality image. Each image data that has been improved will be feature extracted using ResNet and VGG to produce the best model. Furthermore, the classification model development process is carried out using CNN architecture as the model architecture. We also provide innovation by using object detection technology. Which uses artificial neural networks. Here we train the model using aerial video datasets of oil palm plants obtained from drones. Furthermore, to evaluate the performance of the above technique, it is proposed to use the mapping model, precision and accuracy evaluation obtained in the test phase[2]

关键词： YOLO Productivity Technological innovation Oils Multimedia systems Plantations Feature extraction Informatics Monitoring Drones

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Resilient Navigation Based on Multimodal Measurements and Degradation Identification for High-Speed Autonomous Race Cars

Resilient Navigation Based on Multimodal Measurements and De...

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IEEE Symposium on Intelligent Vehicle

作者： Daegyu Lee Hyunwoo Nam Chanhoe Ryu Sungwon Nah D. Hyunchul Shim Department of Electrical Engineering Korea Advanced Institute of Science and Technologies (KAIST) Daejeon Republic of Korea Robotics Program KAIST Daejeon Republic of Korea

This paper presents a localization system robust against unreliable measurements and a resilient navigation system recovering from localization failures for Indy autonomous challenge (IAC). The IAC is a competition with full-scale autonomous race cars that drive at speeds up to 300 kph. Owing to high-speed and heavy vibration in the car, a GPS/INS system is prone to degrade causing critical localization errors, which leads to catastrophic *** order to address this issue, we propose a robust localization system that probabilistically evaluates the credibility of multi-modal measurements. At a correction step of the Kalman filter, a degradation identification method with a novel hyper-parameter derived from Bayesian decision theory is introduced to choose the most credible measurement values in real-time. Since the racing condition is so harsh that even our robust localization method can fail for a short period of time, we present a resilient navigation system that enables the race car to continue to follow the race track in the event of a localization failure. Our system uses direct perception information in planning and execution until the completion of localization *** proposed localization system is first validated in a simulation with real measurement data contaminated by large artificial noises. The experimental validation during an actual race is also presented. The last part of our paper shows the results from the real-world tests where our system recovers from failures and prevents accidents in real-time, which proves the resilience of the proposed navigation system.

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Monocular Vision-based Obstacle Avoidance Scheme for Micro Aerial Vehicle Navigation

Monocular Vision-based Obstacle Avoidance Scheme for Micro A...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Karlsson, Samuel Kanellakis, Christoforos Mansouri, Sina Sharif Nikolakopoulos, George Lulea University of Technology Robotics and Artificial Intelligence Team Department of Computer Science Electrical and Space Engineering SE-97187 Sweden

ISBN: (纸本)9780738131153

One of the challenges in deploying Micro Aerial Vehicless (MAVs) in unknown environments is the need of securing for collision-free paths with static and dynamic obstacles. This article proposes a monocular vision-based reactive planner for MAVs obstacle avoidance. The avoidance scheme is structured around a Convolution Neural Network (CNN) for object detection and classification (You Only Lock Once (YOLO)), used to identify the bounding box of the objects of interest in the image plane. Moreover, the YOLO is combined with a Kalman filter to robustify the object tracking, in case of losing the boundary boxes, by estimating their position and providing a fixed rate estimation. Since MAVs are fast and agile platforms, the object tracking should be performed in real-time for the collision avoidance. By processing the information of the bounding boxes with the image field of view and applying trigonometry operations, the pixel coordinates of the object are translated to heading commands, which results to a collision free maneuver. The efficacy of the proposed scheme has been extensively evaluated in the Gazebo simulation environment, as well as in experimental evaluations with a MAV equipped with a monocular camera. © 2021 IEEE.

关键词： Antennas

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An Assessment of Patent Scoring Using Natural Language programming

An Assessment of Patent Scoring Using Natural Language Progr...

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2022 Portland International Conference on Management of engineering and Technology, PICMET 2022

作者： Khongamnuaisak, Lertchai Pentrakoon, Duanghathai Sinthupinyo, Sukree Suanpong, Kwanrat Chulalongkorn University Technopreneurship and Innovation Management Program Graduate School Bangkok Thailand Chulalongkorn University Faculty of Science Department of Materials Science Bangkok Thailand Faculty of Engineering Chulalongkorn University Department of Computer Engineering Bangkok Thailand Chulalongkorn Business School Commerce Department Bangkok Thailand

ISBN: (数字)9781890843410

ISBN: (纸本)9781890843410

Patent has been an increasingly important role in the world because it is not only significant to protect the invention of the company's business but also to generate revenue from the commercialization. WIPO (2018) reports that the repository has many patents so, to assess patent, it consumes time and requires various expertise. Generally, several models have been developed to address this matter, which to assess using a questionnaire tool for portfolios by human. Perhaps, there is not precise because it is assessed base on personal bias or previous experience of expertise. So that, occurs bias any limitation exists that our research will address by artificial intelligence. Thus, this research applies a Natural Language programming to assess for commercial of the patent. Then, the obtained data is used to assigned factors and calculate the model for assessing the commercialization of patent. This finding should deliver an alternative effective patent assessment, which is tool addresses, some current deficiency patent assessment for commercialization. © 2022 PICMET.

关键词： Patents and inventions

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Cardiovascular Disease Analysis Using Correlational Analysis and Association Rules Mining for In-depth Analysis to Identify Predominant Variables

Cardiovascular Disease Analysis Using Correlational Analysis...

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computer science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Boby Siswanto Haryono Soeparno Nesti F. Sianipar Widodo Budiharto Computer Science Department BINUS Graduate Program- Computer Science Bina Nusantara University Jakarta Indonesia Food Technology Department Engineering Faculty Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Cardiovascular disease is one of the dangerous non-communicable disorders or diseases that has become one of the causes of death worldwide. Various studies have been conducted to prevent cardiovascular disease in the world. This study analyzed cardiovascular disease medical record data from the Kaggle public dataset by implementing correlational analysis combined with association rule mining to identify variables that are the predominant cause of cardiovascular disease. Correlational analysis can analyze the interrelationships between variables in a dataset, but not in depth. Association rule mining can identify the interrelationships of variables in the form of frequent item sets, which can be calculated for their support and confidence values. The result of this study is a combination of correlation analysis with association rule mining that can identify predominant variables to cause cardiovascular disease. Found that the variable gender=woman, height=short (<165 cm), and age=middle (45-60 years) are more likely to be affected by cardiovascular disease. The variable gender=woman with height=short indicates a 76.07% probability of developing cardiovascular disease.

关键词： computer science Correlation Itemsets Cardiovascular diseases Data mining Information technology

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Twenty years of e-learning in health science: A bibliometric 7

Twenty years of e-learning in health science: A bibliometric

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Maulana, Fairuz Iqbal Febriantono, M. Aldiki Raharja, Dwi Risza Budi Khaeruddin Herasmara, Ridho Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health sciences field, which Scopus index. © 2022 Elsevier B.V.. All rights reserved.

关键词： Publishing

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