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Individual Alpha Frequency tACS modifies the detection of space-time optical illusion

Brain Stimulation 2025年第1期18卷 360-360页

作者： Scoccia, Adriano Neri, Francesco Catrambone, Vincenzo Cinti, Alessandra Benelli, Alberto Romanella, Sara Grabot, Laetitia Valenza, Gaetano Smeralda, Carmelo Luca Santarnecchi, Emiliano van Wassenhove, Virginie Rossi, Simone Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab) Department of Medicine Surgery and Neuroscience Neurology and Clinical Neurophysiology Section University of Siena Italy Oto-Neuro-Tech Conjoined Lab Policlinico Le Scotte University of Siena Italy Department of Information Engineering University of Pisa Bioengineering & Robotics Research Center “E. Piaggio” Pisa Italy Precision Neuroscience & Neuromodulation Program Massachusetts General Hospital Harvard Medical School Boston MA USA Cognitive Neuroimaging Unit CEA DRF/Joliot NeuroSpin INSERM Université Paris-Saclay 91191 Gif-sur-Yvette France Department for Cognitive Neuroscience Faculty of Biology & Cognitive Interaction Technology Center of Excellence Bielefeld University Bielefeld Germany

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Strengthening of cruciform welded joints by externally bonded carbon fiber sheets using vartm technique 7

Strengthening of cruciform welded joints by externally bonde...

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7th Asia-Pacific Conference on FRP in Structures, APFIS 2019

作者： Ozawa, T. Thay, V. Nakamura, H. Matsui, T. Miyagawa, M. Graduate School of Urban Environmental Sciences Tokyo Metropolitan University 1-1 Minami-Osawa Hachioji-shi Tokyo192-0397 Japan Advanced Composites Technical Department Toray Industries Inc. 2-1-1 Nihonbashi Muromachi Chuo-ku Tokyo103-8666 Japan Robotics Program Tokyo Metropolitan College of Industrial Technology 8-17-1 Minami-Senju Arakawa-ku Tokyo116-8523 Japan

ISBN: (纸本)9780648752899

This paper deals with the development of strengthening steel structures before the initiation of fatigue crack by externally bonded carbon fiber (CF) sheets using Vacuum assisted Resin Transfer Molding (VaRTM) technique on typical non-load-carrying cruciform welded joints. The reduction of stress concentration at weld toe was analytically and experimentally investigated. In analytical study, finite element (FE) models were simulated from a number of image data (approximately 90 photos) taken from actual experimental specimens by digital camera. In experimental study, the target specimens of non-load-carrying cruciform welded joints were fabricated in considering the development length and taper end and subjected to static and cyclic load. In static tests, good agreement of reduction of stress concentration at weld toe between analytical and experimental results can be confirmed. In fatigue tests, significant improvement of fatigue lives of strengthened specimens have been confirmed compared to non-strengthened specimens. From this study, the proposed strengthening method by CF sheets using VaRTM technique in welded joins can be used as fatigue countermeasure in practical use. © APFIS 2019. All right reserved.

关键词： Stress concentration

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Automating Care by Self-maintainability for Full Laboratory Automation

arXiv

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arXiv 2025年

作者： Ochiai, Koji Tahara-Arai, Yuya Kato, Akari Kaizu, Kazunari Kariyazaki, Hirokazu Umeno, Makoto Takahashi, Koichi Kanda, Genki N. Ozaki, Haruka Laboratory for Biologically Inspired Computing RIKEN Center for Biosystems Dynamics Research 6-7-1 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Bioinformatics Laboratory Institute of Medicine University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Ph.D. Program in Humanics School of Integrative and Global Majors University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Laboratory Automation Suppliers’ Association 2-1-8 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Cell Modeling and Simulation Group Exploratory Research Center on Life and Living Systems National Institutes of Natural Sciences 5-1 Higashiyama Myodaiji Aichi Okazaki444-8787 Japan Robotics Division YASKAWA Electric Corporation 2-1 Kurosaki Shiroishi Yahatanishi-ku Kitakyushu Fukuoka806-0004 Japan BAIKEIDO LLC 3-8-1 Asano Kokurakita-ku Kitakyushu Fukuoka802-0001 Japan Graduate School of Media and Governance Keio University 5322 Endo Fujisawa-shi Kanagawa252-0882 Japan Medical Research Laboratory Institute of Integrated Research Institute of Science Tokyo 1-5-45 Yushima Bunkyo-ku Tokyo113-8519 Japan Center for Artificial Intelligence Research University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan

The automation of experiments in life sciences and chemistry has significantly advanced with the development of various instruments and AI technologies. However, achieving full laboratory automation, where experiments conceived by scientists are seamlessly executed in automated laboratories, remains a challenge. We identify the lack of automation in planning and operational tasks—critical human-managed processes collectively termed "care"—as a major barrier. Automating care is the key enabler for full laboratory automation. To address this, we propose the concept of self-maintainability (SeM): the ability of a laboratory system to autonomously adapt to internal and external disturbances, maintaining operational readiness akin to living cells. A SeM-enabled laboratory features autonomous recognition of its state, dynamic resource and information management, and adaptive responses to unexpected conditions. This shifts the planning and execution of experimental workflows, including scheduling and reagent allocation, from humans to the system. We present a conceptual framework for implementing SeM-enabled laboratories, comprising three modules—Requirement manager, Labware manager, and Device manager—and a Central manager. SeM not only enables scientists to execute envisioned experiments seamlessly but also provides developers with a design concept that drives the technological innovations needed for full automation. Copyright © 2025, The Authors. All rights reserved.

关键词： Information management

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Frequency dependent reduction of cyber-sickness nausea in Virtual Reality by transcranial oscillatory stimulation of the vestibular cortex

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Brain Stimulation 2023年第1期16卷 260-260页

作者： Benelli, Alberto Neri, Francesco Cinti, Alessandra Romanella, Sara M. Giannotta, Alessandro De Monte, David Mandalà, Marco Smeralda, Carmelo Prattichizzo, Domenico Rossi, Simone Santarnecchi, Emiliano Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab) Unit of Neurology and Clinical Neurophysiology Department of Medicine Surgery and Neuroscience University of Siena Italy Oto-Neuro-Tech Conjoined Lab Policlinico Le Scotte University of Siena Italy Precision Neuroscience & Neuromodulation Program Gordon Center for Medical Imaging Massachusetts General Hospital Harvard Medical School Boston MA USA Otolaryngology Department of Medicine Surgery and Neuroscience Neurology and Clinical Neurophysiology Section University of Siena Italy Siena Robotics and Systems (SiRS) Lab Department of Information Engineering and Mathematics University of Siena Siena Italy

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Using Bacteria Foraging Optimization in Gesture Reconfiguration from Joint Failure for Semi-Humanoid Robot

Using Bacteria Foraging Optimization in Gesture Reconfigurat...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Wisanu Jutharee Boonserm Kaewkamnerdpong Jumpol Polvichai Thavida Maneewarn Institute of Field Robotics King Mongkut's University of Technology Thonburi Bangkok Thailand Biological Engineering Program Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

Joint failure problem in humanoid robots could often occur in real application. An approach for fault recovery is performing gesture reconfiguration on a redundant manipulator of humanoid robots. In this study, we proposed a gesture reconfiguration method based on bacteria foraging optimization algorithm. After joint failure, we locked the failed joint in place and used the BFOA-based gesture reconfiguration to find a new suitable gesture configuration for the remaining joints. We demonstrated the gesture reconfiguration from joint failure on the Namo robot, which is a semi-humanoid robot for performing emblematic gestures as a receptionist robot. Four emblematic gestures, including the Thai greeting, salute, bye, and side invite gestures, were demonstrated. The experimental results showed that the BFOA-based gesture reconfiguration could generate a suitable gesture configuration for all four gestures; the resulting gestures are close to the original gestures. We investigated further on tuning the number of population size in BFOA. We varied the number of population size as 15, 25, 50, and 100 and found that although the larger population size could result in better gestures than the smaller size, the improvement in gesture similarity were not significant so it may be more efficient to use the smaller size. This could be owing to the performance of bacteria foraging optimization algorithm.

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RRNet: Repetition-reduction network for energy efficient decoder of depth estimation

arXiv

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arXiv 2019年

作者： Oh, Sangyun Kim, Hye-Jin S. Lee, Jongeun Kim, Junmo School of Electrical and Computer Engineering UNIST Ulsan Korea Republic of Neural Processing Research Center Seoul National University Seoul Korea Republic of Robotics Program School of Electrical Engineering KAIST Daejeon Korea Republic of Artificial Intelligence Laboratory ETRI Daejeon Korea Republic of

We introduce Repetition-Reduction network (RRNet) for resource-constrained depth estimation, offering significantly improved efficiency in terms of computation, memory and energy consumption. The proposed method is based on repetition-reduction (RR) blocks. The RR blocks consist of the set of repeated convolutions and the residual connection layer that take place of the pointwise reduction layer with linear connection to the decoder. The RRNet help reduce memory usage and power consumption in the residual connections to the decoder layers. RRNet consumes approximately 3.84 times less energy and 3.06 times less memory and is approaximately 2.21 times faster, without increasing the demand on hardware resource relative to the baseline network [1], outperforming current state-of-the-art lightweight architectures such as SqueezeNet [2], ShuffleNet [3], MobileNetv2 [4] and PyDNet [5]. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy utilization

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The agile robotics for industrial automation competition

The agile robotics for industrial automation competition

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作者： Harrison, William Downs, Anthony Schlenoff, Craig NIST Intelligent Systems Division United States Robotics Systems for Smart Manufacturing Program Agility Performance of Robotic Systems Cognition and Collaboration Systems Group Intelligent Systems Division National Institute of Standards and Technology United States United States

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Evaluation of an adjustable support shoulder exoskeleton on static and dynamic overhead tasks

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2018年第1期62卷 804 - 808页

作者： Logan Van Engelhoven Nathan Poon Homayoon Kazerooni Alan Barr David Rempel Carisa Harris-Adamson University of California Berkeley Human Engineering and Robotics Lab University of California Berkeley/San Francisco Ergonomics Graduate Research Training Program

Introduction: Overhead tasks increase the risk of work related musculoskeletal disorders to industrial workers. A shoulder supporting exoskeleton with adjustable and angle dependent torque (referred to as shoulderX in this paper for brevity) was designed and built at the University of California Berkeley Human Engineering and robotics Laboratory for workers performing overhead tasks. shoulderX was designed specifically to reduce the exposure to large muscle exertion forces on the shoulder complex from overhead work. Methods: We evaluated shoulderX by measuring the muscle activation of the upper trapezius (UT), anterior deltoid (AD), triceps long head (TR), and infraspinatus (IF) during static and dynamic overhead tasks. Thirteen male subjects with experience in the construction or manufacturing industries were recruited to perform overhead tasks using light (.45 kg) and heavy (2.25 kg) weight tools with four exoskeleton support levels (0, 8.5, 13.0, 20.0 Nm peak torque). Results: During all conditions, the wearer’s shoulder flexor muscle activity of UT, AD were reduced with increasing strength of shoulderX by up to 80%. Subjects unanimously preferred the use of shoulderX over the unassisted condition for all task types (static and dynamic overhead tasks) and tool weights (.45 kg and 2.25 kg). Conclusion: shoulderX reduces the wearer’s primary muscle activity in overhead static and dynamic work and results in a more desirable and balanced pattern of shoulder complex activation. This investigation indicates that shoulderX reduces the risk of work related shoulder injuries during overhead tasks.

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Decision-Level Fusion Method for Emotion Recognition using Multimodal Emotion Recognition Information 15

Decision-Level Fusion Method for Emotion Recognition using M...

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15th International Conference on Ubiquitous Robots, UR 2018

作者： Song, Kyu-Seob Nho, Young-Hoon Seo, Ju-Hwan Kwon, Dong-Soo Department of Robotics Program Korea Advanced Institute of Science and Technology Human-Robot Interaction Research Center Korea Republic of Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Human-Robot Interaction Research Center Korea Republic of

ISBN: (纸本)9781538663349

Human emotion recognition is an important factor for social robots. In previous research, emotion recognizers with many modalities have been studied, but there are several problems that make recognition rates lower when a recognizer is applied to a robot. This paper proposes a decision level fusion method that takes the outputs of each recognizer as an input and confirms which combination of features achieves the highest accuracy. We used EdNet, which was developed in KAIST based Convolutional Neural Networks (CNNs), as a facial expression recognizer and a speech analytics engine developed for speech emotion recognition. Finally, we confirmed a higher accuracy 43.40% using an artificial neural network (ANN) or the k-Nearest Neighbor (k-NN) algorithm for classification of combinations of features from EdN et and the speech analytics engine. © 2018 IEEE.

关键词： Engines

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Compositional planning in Markov decision processes: Temporal abstraction meets generalized logic composition

arXiv

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arXiv 2018年

作者： Liu, Xuan Fu, Jie Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA United States

In hierarchical planning for Markov decision processes (MDPs), temporal abstraction allows planning with macro-actions that take place at different time scale in form of sequential composition. In this paper, we propose a novel approach to compositional reasoning and hierarchical planning for MDPs under co-safe temporal logic constraints. In addition to sequential composition, we introduce a composition of policies based on generalized logic composition: Given sub-policies for sub-tasks and a new task expressed as logic compositions of subtasks, a semi-optimal policy, which is optimal in planning with only sub-policies, can be obtained by simply composing sub-polices. Thus, a synthesis algorithm is developed to compute optimal policies efficiently by planning with primitive actions, policies for sub-tasks, and the compositions of sub-policies, for maximizing the probability of satisfying constraints specified in the fragment of co-safe temporal logic. We demonstrate the correctness and efficiency of the proposed method in stochastic planning examples with a single agent and multiple task specifications. Copyright © 2018, The Authors. All rights reserved.

关键词： Markov processes

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