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Enhanced Attitude Stabilization of Quadrotors Using a Single-Axis Constraint Moment Disturbance Obserner

IEEJ Transactions on Industry Applications 2024年第4期144卷 257-264页

作者： Ichiryu, Atsuhiro Shimada, Akira Electrical Engineering and Computer Science Graduate School of Engineering and Science Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan Dept. of Engineering and Design Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan

This study proposes a maintaining a quadrotor’s attitude system using a ‘moment disturbance observer’ aimed at enhancing stability. In recent years, quadrotors have become increasingly prevalent in sectors such as agriculture, surveying, logistics, aerial photography, infrastructure inspection, and security. However, with their growing, there have been concerns about potential physical and human harm stemming from accidents. The Ministry of Land, Infrastructure, Transport, and Tourism has reported accidents attributed to challenging maneuvering conditions that have resulted in crashes. This study aims to develop a quadrotor that can maintain a stable attitude during sudden and significant alterations in its orientation. We suggest employing a moment disturbance observer to estimate the necessary moments for stable attitude maintenance. Numerical simulation results show that the proposed method surpasses traditional PID control in terms of attitude stabilization. Furthermore, this method resulted in superior attitude stability in single-axis experiments with a mechanically constrained quadrotor compared to conventional PID control methods. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Aerial photography

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Heart Sound Analysis for Smart Stethoscope in Mobile Environments 8

Heart Sound Analysis for Smart Stethoscope in Mobile Environ...

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8th IEEE International Conference on Smart Cloud, SmartCloud 2023

作者： Lee, Sungmin Shin, Younghoon Qun, Wei Lee, Miran Graduate School of IT Convergence Engineering Daegu University Gyeongsan Korea Republic of Dept. of Biomedical Engineering Keimyung University Daegu Korea Republic of 3Dept. of Computer & Information Engineering Daegu University Gyeongsan Korea Republic of

This study proposes a method of analysis method that can be monitored using bio-signals in mobile environments. The proposed model is designed in a parallel structure that utilizes PPG and PCG signals related to the h... 详细信息

ISBN: (纸本)9798350313505

关键词： Internet of things

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Causes and Consequences of IPD Mismatch in XR Devices

Causes and Consequences of IPD Mismatch in XR Devices

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International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Wilcox, Laurie M. Allison, Robert S. Department of Psychology York University TorontoM3J1P3 Canada Dept. of Electrical Engineering and Computer Science York University TorontoM3J1P3 Canada

Binocular 3D display systems, including virtual, augmented and mixed reality (collectively referred to as XR) devices support stereoscopic depth perception by presenting dichoptic views separately to the two eyes rendered according to their vantage points. A common human factors issue is a mismatch between the observer’s physical interpupillary distance (IPD) and 1) the separation between the device optics and 2) the rendered/captured content. This paper provides a theoretical review of the importance and consequences for user experience of accurately estimating IPD and incorporating it into HMD adjustments, calibration and rendering. © 2024, John Wiley and Sons Inc. All rights reserved.

关键词： Stereocenters

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Muscle-Guided Guitar Pedalboard: Exploring Interaction Strategies Through Surface Electromyography and Deep Learning

Muscle-Guided Guitar Pedalboard: Exploring Interaction Strat...

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International Conference on New Interfaces for Musical Expression, NIME 2024

作者： Lionetti, Davide Belluco, Paolo Zanoni, Massimiliano Turchet, Luca Dept. of Art and Science University of Ghent Ghent Belgium LWT3 Milan Italy Dept. of Electronics Information and Bioengineering Polytechnic University of Milan Milan Italy Dept. of Information Engineering and Computer Science University of Trento Trento Italy

This paper explores a method to innovate the conventional interaction with a guitar pedalboard. By analyzing muscular contractions tracked via surface Electromyography (sEMG) wearable sensors, we aimed to investigate how to dynamically track guitarists’ sonic intentions to automatically control the guitar sound. Two Recurrent Neural Networks based on Bidirectional Long-Short Term Memory were developed to analyze sEMG signals in real-time. The system was designed as a digital musical instrument that calibrates itself to each user during an initial training process. During training musicians provide their gestural vocabulary, associating each gesture to a corresponding pedalboard preset. The selection of the most effective features, in synergy with the best set of muscles, was conducted to optimize the learning rate of the system. The system was assessed with a user study encompassing seven expert guitar players. Results showed that, on average, participants appreciated the concept underlying the system and deemed it to be able to foster their creativity. © 2024, International Conference on New Interfaces for Musical Expression. All rights reserved.

关键词： Long short-term memory

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Verification of Animal External Ear Model-based Microphone Sensor for Hazardous Sound Detection 6

Verification of Animal External Ear Model-based Microphone S...

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6th International Symposium on Advanced Technologies and Applications in the Internet of Things, ATAIT 2024

作者： Yamada, Miho Kumaki, Takeshi Kageyama, Kyosuke Graduate School of Science and Engineering Kindai University 3-4-1 Kowakae Higashi-Osaka Osaka Japan Dept. of Electronic and Computer Engineering Ritsumeikan University 1-1-1 Noji-Higashi Shiga Kusatsu Japan Dept. of Electrical Electronic and Communication Engineering Kindai University 3-4-1 Kowakae Higashi-Osaka Osaka Japan

Hazardous sounds represent a particular type of danger signal and should be heard clearly to ensure safety. Hearing-impaired people can be involved in accidents. This is exacerbated by the fact that they may have difficulty hearing hazardous sounds. Therefore, they spend time with a hearing-assistance dog in their daily lives. However, the number of hearing-assistance dogs has decreased recently, and they are less known in society and they may even be prevented from entering public facilities. Therefore, an animal external ear model-based mobile device that can detect hazardous sounds has been proposed. This device can alert the hearing-impaired person. In this paper, the animal external attachment with a human- and a cat-external ear model-verified for hazardous sound detection accuracy by microphone sensor is presented. Microphone sensors with and without a human- and a cat-external ear model are used. An ambulance siren and a bicycle bell are used as the hazardous sounds, and the spectral envelopes of each recorded sound are compared. The results show that the animal external ear model-based microphone sensor can more effectively detect the frequency features of the ambulance siren and the bicycle bell. A microphone sensor attached an external attachment with a human-external ear model can detect 2 ∼ 3 kHz frequency features with the highest sound pressure compared to the other microphones, regardless of the distance between the microphone sensor and the sound source. Also, a microphone sensor attached an external attachment with a cat-external ear model can detect wide range of frequencies with the highest sound pressure compared to the other microphone sensors, regardless of the distance between the microphone sensor and the sound source. © 2024 Copyright for this paper by its authors.

关键词： Bicycles

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Utilizing Machine Learning to Enhance Infrastructure Resilience in Cold Regions 20

Utilizing Machine Learning to Enhance Infrastructure Resilie...

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20th International Conference on Cold Regions engineering: Sustainable and Resilient engineering Solutions for Changing Cold Regions, ICCRE 2024

作者： Shohel Rana, Md Gudla, Charan Ahmed, Feroz Nobi, Mohammad Nur Dept. of Computing and Software Engineering Florida Gulf Coast Univ. Fort MyersFL United States Dept. of Computer Science and Engineering Mississippi State Univ. StarkvilleMS United States Prediction 3D Technologies BiloxiMS United States Dept. of Computer Science Univ. of Texas at San Antonio San AntonioTX United States

ISBN: (纸本)9780784485460

In the challenging domain of engineering, where cold regions present formidable challenges, we confront the relentless forces of nature. From sub-zero temperatures to the unpredictable dance of snowfall and the silent buildup of ice, these regions demand innovative solutions to fortify the resilience of critical infrastructure. This initiative harnesses the potential of cutting-edge technology and leverages the extensive historical weather data tapestry. It introduces a pioneering strategy by integrating machine learning algorithms with extensive weather data, steering cold region engineering into an era defined by foresight and adaptability. This paper studies a transformative approach designed to forecast, prevent, and ultimately enhance infrastructure resilience in the face of rigid cold. Addressing the distinct challenges of cold region engineering, arising from harsh winter conditions such as extreme cold temperature, snowfall, and ice accumulation, we offer a comprehensive study using machine learning algorithms applied to historical weather data to construct a deeper analysis model capable of highlighting adverse weather effects. This, in turn, covers the way for optimized resource allocation, streamlined maintenance planning, and design enhancements. Our proposed study follows a systematic process, encompassing meticulous data collection, appropriate feature selection, and aiming seamless integration of the model into existing infrastructure management systems. Additionally, it facilitates the implementation of efficient and proactive measures to mitigate the impact of severe weather conditions on infrastructure. The paper also conducts three different hypotheses testing: temperature impact hypothesis, precipitation influence hypothesis, and ice accumulation and infrastructure resilience hypothesis, propelling engineering practices to new heights, particularly in the face of challenging cold environments. © ASCE.

关键词： Snow

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Higher-order interactions (Bipolar or not) in abstract argumentation: A state of the art

Journal of Applied Logics

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Journal of Applied Logics 2021年第6期8卷 1339-1435页

作者： Cayrol, Claudette Cohen, Andrea Lagasquie-Schiex, Marie-Christine IRIT Université Toulouse 3 Toulouse France Institute for Computer Science and Engineering CONICET-UNS Dept. of Computer Science and Engineering Universidad Nacional del Sur Bahía Blanca Argentina

In Dung’s seminal work, an argumentation framework was defined by a set of abstract arguments and a binary (and also abstract) relation between these arguments, called attack relation and expressing conflicts between arguments. Due to its simplicity and the power of its abstraction, this representation has been intensively used by the community for over 25 years. Another advantage of this approach is the ease with which we can extend the framework, weighting arguments or attacks, using priorities or pre-orderings on the sets of arguments, considering that these interactions are no longer binary ones over the set of arguments (e.g. collective attacks), adding new kinds of interactions (e.g. supports), and proposing that the targets of these interactions can also be interactions themselves (i.e. higher-order interactions). These last two points are the core of this chapter, in which we present a survey of the proposed approaches existing around the notion of higher-order interactions (attacks and supports) in an abstract argumentation framework. © 2021, College Publications. All rights reserved.

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Balancing Real-world Interaction and VR Immersion with AI Vision Robotic Arm 20

Balancing Real-world Interaction and VR Immersion with AI Vi...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yang, Xiaoran Zhan, Yang Iwasaki, Yukiko Shi, Miaohui Tang, Shijie Iwata, Hiroyasu Waseda University Dept. Modern Mechanical Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan Waseda University Dept. Computer Science and Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan

ISBN: (纸本)9798350320831

With the widespread adoption of Virtual Reality (VR) technology, VR devices can be more realistic and make the tasks they perform feel real to the user. It is this sense of realism that makes more and more people are using VR headsets. While using VR devices, the need to interact with the real world will also exist. For example, when people are using a VR headset to study and work, they have a physiological need (thirst, hunger, etc.), and need to interact with reality. But the closed nature of the VR headset causes this interaction to be very disruptive to the immersion of the user's current task. To address this issue, we propose an interaction method that combines an AI vision algorithm and a robotic arm to preserve immersion during task performance in VR. This method addresses the challenge of interacting with the real world while using closed VR devices. Our experiments show that our method outperforms see-through and mapping methods, allowing users to quickly re-immerse themselves after interruptions and reducing interruptions during real-world task performance. Future research will focus on improving this method without sensitization and expanding the range of real-world operations that can be performed. © 2023 IEEE.

关键词： Virtual reality

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Analysis of Power Transformers under Geomagnetically Induced Currents 4

Analysis of Power Transformers under Geomagnetically Induced...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Behjat, Vahid Mostafaei, Mohsen Rezaei-Zare, Afshin Cheema, Muhammad Ali Masood York University Dept. of Electrical Engineering and Computer Science TorontoONM3J 1P3 Canada Northern Transformer Company Dept. of Research and Special Design TorontoONL6A4P5 Canada

ISBN: (纸本)9798350335408

This paper describes the development of a low-frequency model to analyze impacts of Geomagnetically Induced Currents (GIC) on power transformers. GIC causes power transformer core and tank saturation which can conduce to flow of harmonic currents, voltage-control problems, and heating of the transformer internal components, ultimately leading to possible damages and gas relay alarm/operation. To analyze the transformer, first, an accurate low-frequency transient model is developed to allow the flow of GIC in the power transformer windings. The developed transformer transient model is based on the topological representation of the transformer core, flux air paths, and tank and is accurate enough for considering low and mid-frequency transients including GIC. The calculated currents are fed into a Finite Element Model of the transformer developed for the purpose of GIC study in this research work. Utilizing the FEM model, the pattern of electromagnetic flux distribution and hot spots caused by GIC in the transformer core and tank are specified. The extracted characteristic features of the transformer will provide helpful insights into the optimal design and production of power transformers. © 2023 IEEE.

关键词： Power transformers

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Nonparametric Estimation of Local Bandwidth from Level Crossings Sampling

Nonparametric Estimation of Local Bandwidth from Level Cross...

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2023 International Conference on Sampling Theory and Applications, SampTA 2023

作者： Pawlak, Miroslaw Rzepka, Dominik Miskowicz, Marek Agh University of Science and Technology Dept. of Measurement and Electronics Krakow Poland University of Manitoba Canada Dept. of Electrical and Computer Engineering WinnipegR3T 5V6 Canada

ISBN: (纸本)9798350328851

We study the problem of a local bandwidth recovery for nonstationary stochastic signals when the measured information is given in terms of level crossings. We propose a kernel estimate of the local bandwidth from samples generated from level crossings of stochastic signals being the time-warped version of stationary Gaussian processes. The positivity and bandlimited nature of the local intensity is captured by the properly selected class of bandlimited and positive kernel functions. The asymptotic properties of the estimator are derived. © 2023 IEEE.

关键词： Railroad crossings

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