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arXiv 2025年

作者： Shinohara, Shuji Morita, Daiki Hirai, Hayato Kuribayashi, Ryosuke Manome, Nobuhito Moriyama, Toru Nakajima, Yoshihiro Gunji, Yukio-Pegio Chung, Ung-Il School of Science and Engineering Tokyo Denki University Saitama Japan Department of Bioengineering Graduate School of Engineering The University of Tokyo Tokyo Japan Department of Research and Development SoftBank Robotics Group Corp. Tokyo Japan Faculty of Textile Science Shinshu University Ueda Japan Graduate School of Economics Osaka City University Osaka Japan Department of Intermedia Art and Science School of Fundamental Science and Technology Waseda University Tokyo Japan

This study introduces a novel inference framework, designated as Bayesian and inverse Bayesian (BIB) inference, which concurrently performs both conventional and inverse Bayesian updates by integrating symmetry bias into Bayesian inference. The effectiveness of the model was evaluated through a sequential estimation task involving observations sampled from a Gaussian distribution with a stochastically time-varying mean. Conventional Bayesian inference entails a fundamental trade-off between adaptability to abrupt environmental shifts and estimation accuracy during stable intervals. The BIB framework addresses this limitation by dynamically modulating the learning rate through inverse Bayesian updates, thereby enhancing adaptive flexibility. The BIB model generated spontaneous bursts in the learning rate during sudden environmental transitions, transiently entering a high-sensitivity state to accommodate incoming data. This intermittent burst-relaxation pattern functions as a dynamic mechanism that balances adaptability and accuracy. Further analysis of burst interval distributions demonstrated that the BIB model consistently produced power-law distributions under diverse conditions. Such robust scaling behavior, absent in conventional Bayesian inference, appears to emerge from a self-regulatory mechanism driven by inverse Bayesian updates. These results present a novel computational perspective on scale-free phenomena in natural systems and offer implications for designing adaptive inference systems in nonstationary environments. © 2025, CC BY-NC-ND.

关键词： Monte Carlo methods

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Improving energy detection performance using segment of primary user signal energy in wide-band cognitive radio systems

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AIP Conference Proceedings 2023年第1期2579卷

作者： Khaled BaAli Mohammed Abo-Zahhad Mohammed Farrag Sabah Ahmed Phaklen Ehkan Department of Electronics and Communication Engineering Hadhramout University Mukalla Yemen Department of Electronics and Communication Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Engineering King Khalid University Asir – Abha Saudi Arabia Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Advanced Computing CoE Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Pauh Putra Campus Arau Perlis Malaysia

Energy detection based cognitive radio has gained remarkable attention. This is because of its simple implementation and it does not involve any prior knowledge of the detecting signal. Although, it is prone to noise uncertainty. Recently, the use of compressed measurements improved the performance of energy detection. In this paper, we investigate the effect of using a segment of primary user signal energy ƞE on detection performance regarding compression ratios. The simulation results show the detector performance becomes better as ƞE increased. However, increasing ƞE should be bounded, so it does not involve sacrificing the use of the compressed measurement system as a suggestion to improve energy detection performance.

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DSR: Direct Simultaneous Registration for Multiple 3D Images?

arXiv

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arXiv 2021年

作者： Mao, Zhehua Zhao, Liang Huang, Shoudong Fan, Yiting Lee, Alex P.W. Robotics Institute Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia Department of Cardiology Shanghai Chest Hospital Shanghai Jiao Tong University Shanghai China Division of Cardiology Department of Medicine and Therapeutics Prince of Wales Hospital Laboratory of Cardiac Imaging and 3D Printing Li Ka Shing Institute of Health Science Faculty of Medicine The Chinese University of Hong Kong Hong Kong

This paper presents a novel algorithm named Direct Simultaneous Registration (DSR) that registers a collection of 3D images in a simultaneous fashion without specifying any reference image, feature extraction and matching, or information loss or reuse. The algorithm optimizes the global poses of local image frames by maximizing the similarity between a predefined panoramic image and local images. Although we formulate the problem as a Direct Bundle Adjustment (DBA) that jointly optimizes the poses of local frames and the intensities of the panoramic image, by investigating the independence of pose estimation from the panoramic image in the solving process, DSR is proposed to solve the poses only and proved to be able to obtain the same optimal poses as DBA. The proposed method is particularly suitable for the scenarios where distinct features are not available, such as Transesophageal Echocardiography (TEE) images. DSR is evaluated by comparing it with four widely used methods via simulated and in-vivo 3D TEE images. It is shown that the proposed method outperforms these four methods in terms of accuracy and requires much fewer computational resources than the state-of-the-art accumulated pairwise estimates (APE). Codes of DSR are available at https://***/ZH-Mao/DSR. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Investigation of the process of grinding of a char coal obtained from tires waste pyrolysis

Investigation of the process of grinding of a char coal obta...

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Mineral Engineering Conference 2019, MEC 2019

作者： Sidor, J. Budzyń, S. Czosnek, C. Kozub-Budzyń, G. Tora, B. Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Mickiewicza 30 Av. Krakow30-059 Poland Faculty of Energy and Fuels AGH University of Science and Technology Mickiewicza 30 Av. Krakow30-059 Poland Faculty of Geology Geophysics and Environmental Protection AGH University of Science and Technology Mickiewicza 30 Av. Krakow30-059 Poland Faculty of Mining and Geoengineering AGH University of Science and Technology Mickiewicza 30 Av. Krakow30-059 Poland

The paper contains results of examinations of grinding of char obtained from waste car tires. The grinding of the char was conducted in a laboratory vibratory mill of low vibration frequency. The examinations concerned the possibility of using a char as raw material in industry, particularly as a substitute for carbon black applied for the production of rubber. One of the basic parameters characterizing carbon black is particle size distribution as well as specific surface area. In the examinations, the char was obtained with following characteristic sizes of particles: d50 = 2.5 ÷ 9.3 μm, d90 = 13.3 ÷ 35.0 μm and specific surface area 74 ÷ 163 m2/g matching the particle size distribution and specific surface area characteristic of carbon black, which means that in order to grind a char, the vibratory mill can be used. Komentarz [D1]: This terminology is not clear to use in the paper. © Published under licence by IOP Publishing Ltd.

关键词： Carbon black

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VibroSleeve: A wearable vibro-tactile feedback device for arm guidance

VibroSleeve: A wearable vibro-tactile feedback device for ar...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Deepa Prabhu Muhammad Mehedi Hasan Lisa Wise Clare MacMahon Chris McCarthy Faculty of Science Engineering and Technology School of Software Engineering Robotics and Mechatronics Lab Faculty of Health Arts and Design School of Health Sciences Swinburne University of Technology Hawthorn VIC Australia Department of Rehabilitation La Trobe University Melbourne VIC Australia

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Vibro-tactile feedback offers a complementary augmentation cue for motor guidance and training. Motivated by the needs of prosthetic vision rehabilitation, we explore the use of the cylindrical forearm surface to deliver arm guidance cues via vibro-tactile stimulation. We present `VibroSleeve', a novel wearable arm motion guidance aid made up of 4×4 arrangement of vibration coin motors embedded within an elastic sleeve for delivering vibro-tactile patterns to the forearm. In this paper, we present the concept and design of VibroSleeve, along with results of preliminary evaluation. We outline key insights gained into the perceptual aspects of calibration and usable intensity bandwidth critical for reliable interpretation of encoded information. Our results demonstrate feasibility of the approach, and provide foundations for future work on developing the sleeve as a rehabilitation aid for guiding the arm towards visually perceived targets.

关键词： Vibrations Training Pulse width modulation Pattern recognition Prosthetics Visualization Calibration

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Time-of-use pricing for energy storage investment

arXiv

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arXiv 2021年

作者： Zhao, Dongwei Wang, Hao Huang, Jianwei Lin, Xiaojun MIT Energy Initiative Massachusetts Institute of Technology CambridgeMA02139 United States Department of Data Science and Artificial Intelligence Faculty of Information Technology Monash University MelbourneVIC3800 Australia School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States

Time-of-use (ToU) pricing is widely used by the electricity utility to shave peak load. Such a pricing scheme provides users with incentives to invest in behind-the-meter energy storage and to shift peak load towards low-price intervals. However, without considering the implication on energy storage investment, an improperly designed ToU pricing scheme may lead to significant welfare loss, especially when users over-invest the storage, which leads to new energy consumption peaks. In this paper, we will study how to design a social-optimum ToU pricing scheme by explicitly considering its impact on storage investment. We model the interactions between the utility and users as a two-stage optimization problem. To resolve the challenge of asymmetric information due to users’ private storage cost, we propose a ToU pricing scheme based on different storage types and the aggregate demand per type. Each user does not need to reveal his private cost information. We can further compute the optimal ToU pricing with only a linear complexity. Simulations based on real-world data show that the suboptimality gap of our proposed ToU pricing, compared with the social optimum achieved under complete information, is less than 5%. © 2021, CC BY.

关键词： Investments

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Resource Allocation for Edge Computing-Based Blockchain: A Game Theoretic Approach

Resource Allocation for Edge Computing-Based Blockchain: A G...

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IEEE International Conference on Communications Workshops, ICC

作者： Wenlong Guo Zheng Chang Xijuan Guo Dushnatha Nalin K. Jayakody Tapani Ristaniemi College of Information Science and Engineering Yanshan University Qinhuangdao China University of Jyvaskyla Faculty of Information Technology Jyvaskyla Finland School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

Blockchain has been progressively applied to various Internet of Things (IoT) platforms. As the efficiency of the blockchain depends on its computing capability, how to make sure the acquisition of the computational resources and participation of the devices would be the driving force. In this work, an edge computing-based blockchain network is considered, where the edge service provider (ESP) offers computational resources for the miners. The focus is to investigate an efficient incentive mechanism for the miners to purchase the computational resources. Accordingly, a two-stage Stackelberg game is formulated between the miners and ESP. By exploring the Stackelberg equilibrium of the optimal mining strategy under two different mining schemes. The aim is to find the optimal incentive for the ESP and miners to choose auto-fit strategies. Through theoretical analysis and numerical simulation, we demonstrate the effectiveness of the proposed scheme on encouraging devices to participate the Blockchain.

关键词： Games Internet of Things Pricing Standards Computational modeling Radio frequency

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Investigation of the effect of a composite material on rocket fin flutter speed

Investigation of the effect of a composite material on rocke...

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AIAA Propulsion and Energy Forum and Exposition, 2019

作者： Rydz, Zuzanna Palacz, Tomasz Kolusz, Adam Guzik, Mateusz Faculty of Materials Science and Ceramics AGH Space Systems AGH University of Science and Technology al. Mickiewicza 30 Cracow30-059 Poland Faculty of Physics and Computer Science AGH Space Systems AGH University of Science and Technology al. Mickiewicza 30 Cracow30-059 Poland Faculty of Mechanical Engineering and Robotics AGH Space Systems AGH University of Science and Technology al. Mickiewicza 30 Cracow30-059 Poland

ISBN: (纸本)9781624105906

The main purpose of this study is to investigate the effect of various core materials and number of fiberglass layers on flutter characteristics for sounding rocket fins. Three type of composite sandwich cores: PVC foam, Nomex honeycomb and 3D printed core have been used along with varying number of fiberglass layers. Fin samples were manufactured and their frequency response were measured to find bending and torsional natural frequencies. This data has been used in the k-method analysis. As a result, flutter characteristics like critical velocity and frequency were determined for all the samples. © 2019 by American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Foams

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Online Magnetization Surface Identification for a Switched Reluctance Motor

Online Magnetization Surface Identification for a Switched R...

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International Universities Power Engineering Conference (UPEC)

作者： Alecksey Anuchin Andrei Bogdanov Galina Demidova Evgeniy Stolyarov Dimid Surnin Yuriy Vagapov Department of Electric Drives Moscow Power Engineering Institute Moscow Russia Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Faculty of Art Science and Technology Wrexham Glyndwr University Wrexham UK

ISBN: (数字)9781728110783

ISBN: (纸本)9781728110790

The precise control of switched reluctance motor requires information about the magnetization surface as a function of rotor angular position and current. The surface can be obtained performing offline tests; however, it demands specialized mechanical equipment and time for commissioning. Moreover, the magnetization surface may be changed with the varying of the rotor and stator temperatures, which affect their dimensions and, therefore, the airgap variation. That is why the online estimation of the magnetization surface is desirable. This paper proposes the identification method operating in parallel with the model predictive current control system utilizing the magnetization map. Any error between the referenced and obtained currents is used to correct the reference points of the two-dimensional array representing the magnetization surface. The proposed method was examined using a simulation model and operated online in parallel with the primary control system driving the electrical machine.

关键词： Magnetization Reluctance motors Rotors Pulse width modulation Couplings Torque

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Data-driven color augmentation for H&E stained images in computational pathology

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Journal of Pathology Informatics 2023年 14卷 100183-100183页

作者： Marini, Niccolò Otalora, Sebastian Wodzinski, Marek Tomassini, Selene Dragoni, Aldo Franco Marchand-Maillet, Stephane Morales, Juan Pedro Dominguez Duran-Lopez, Lourdes Vatrano, Simona Müller, Henning Atzori, Manfredo Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland Centre Universitaire d'Informatique University of Geneva Geneva Switzerland Support Center for Advanced Neuroimaging University Institute of Diagnostic and Interventional Neuroradiology Bern Switzerland Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Department of Information Engineering Engineering Faculty Università Politecnica delle Marche Ancona Italy Robotics and Technology of Computers Lab ETSII-EPS Universidad de Sevilla Sevilla Spain SCORE Lab I3US Universidad de Sevilla Spain Pathology Unit Gravina Hospital Caltagirone ASP Catania Italy Medical Faculty University of Geneva Geneva Switzerland Department of Neurosciences University of Padua Padua Italy

Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs are high-resolution digitized histopathology images, stained with chemical reagents to highlight specific tissue structures and scanned via whole slide scanners. The application of different parameters during WSI acquisition may lead to stain color heterogeneity, especially considering samples collected from several medical centers. Dealing with stain color heterogeneity often limits the robustness of methods developed to analyze WSIs, in particular Convolutional Neural Networks (CNN), the state-of-the-art algorithm for most computational pathology tasks. Stain color heterogeneity is still an unsolved problem, although several methods have been developed to alleviate it, such as Hue-Saturation-Contrast (HSC) color augmentation and stain augmentation methods. The goal of this paper is to present Data-Driven Color Augmentation (DDCA), a method to improve the efficiency of color augmentation methods by increasing the reliability of the samples used for training computational pathology models. During CNN training, a database including over 2 million H&E color variations collected from private and public datasets is used as a reference to discard augmented data with color distributions that do not correspond to realistic data. DDCA is applied to HSC color augmentation, stain augmentation and H&E-adversarial networks in colon and prostate cancer classification tasks. DDCA is then compared with 11 state-of-the-art baseline methods to handle color heterogeneity, showing that it can substantially improve classification performance on unseen data including heterogeneous color variations. © 2022 The Authors

关键词： Color augmentation Computational pathology Deep learning Digital pathology Histopathology Stain variability

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