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arXiv 2023年

作者： Lee, Ung Hee Shepherd, Tor Kim, Sangbae De, Avik Su, Hao Gregg, Robert Mooney, Luke Rouse, Elliott Neurobionics Lab. University of Michigan Ann ArborMI48109 United States Department of Mechanical Engineering University of Michigan United States The Robotics Institute University of Michigan United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Lab of Biomechatronics and Intelligent Robotics Department of Mechanical Engineering and Aerospace Engineering North Carolina State University RaleighNC27695 United States Department of Electrical Engineering and Computer Science University of Michigan United States Dephy Inc. MaynardMA01754 United States

A key step in the development of lightweight, high performance robotic systems is the modeling and selection of permanent magnet brushless direct current (BLDC) electric motors. Typical modeling analyses are completed a priori, and provide insight for properly sizing a motor for an application, specifying the required operating voltage and current, as well as assessing the thermal response and other design attributes e.g. transmission ratio). However, to perform these modeling analyses, proper information about the motor’s characteristics are needed, which are often obtained from manufacturer datasheets. Through our own experience and communications with manufacturers, we have noticed a lack of clarity and standardization in modeling BLDC motors, compounded by vague or inconsistent terminology used in motor datasheets. The purpose of this tutorial is to concisely describe the governing equations for BLDC motor analyses used in the design process, as well as highlight potential errors that can arise from incorrect usage. We present a power-invariant conversion from phase and line-to-line reference frames to a familiar q-axis DC motor representation, which provides a "brushed" analogue of a three phase BLDC motor that is convenient for analysis and design. We highlight potential errors including incorrect calculations of winding resistive heat loss, improper estimation of motor torque via the motor’s torque constant, and incorrect estimation of the required bus voltage or resulting angular velocity limitations. A unified and condensed set of governing equations is available for designers in Appendix A. The intent of this work is to provide a consolidated mathematical foundation for modeling BLDC motors that addresses existing confusion and fosters high performance designs of future robotic systems. © 2023, CC BY-NC-ND.

关键词： Design

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Face preference detection task based on EEG energy analysis in the source domain

Face preference detection task based on EEG energy analysis ...

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

作者： Pengchao Wang Junkongshuai Wang Lu Wang Wei Mu Gege Zhan Xueze Zhang Lan Niu Jianxiong Bin Zhiyan Dong Lihua Zhang Jie Jia Zhongxue Gan Xiaoyang Kang MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI & Robotics Ministry of Education Shanghai Engineering Research Center of AI & Robotics Institute of AI and Robotics Academy for Engineering & Technology Fudan University Shanghai China Ji Hua Laboratory Foshan China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai China Yiwu Research Institute of Fudan University Yiwu City China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou China

Facial stimulation can produce specific event-related potential (ERP) component N170 in the fusiform gyrus region. However, the role of the fusiform gyrus region in facial preference tasks is not clear at present, and the current research of facial preference analysis based on EEG signals is mostly carried out in the scalp domain. This paper explores whether the region of the fusiform gyrus is involved in processing face preference emotions in terms of the distribution of energy over the source domain, and finds that the pars orbitalis cortex is most energetically active in the face preference task and that there are significant differences between the left and right *** Relevance— The role of pars orbitalis in facial preference may help doctors determine whether the pars orbitalis cortex is lost in clinical practice.

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Dimming the Lights: 2D Simulations of Deflagrations of Hybrid C/O/Ne White Dwarfs using FLASH

arXiv

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arXiv 2023年

作者： Feldman, Catherine Gutierrez, Nathanael Eisenberg, Ellis Willcox, Donald E. Townsley, Dean M. Calder, Alan C. Department of Physics and Astronomy Stony Brook University Stony BrookNY11794-3800 United States Institute for Advanced Computational Science Stony Brook University Stony BrookNY11794-3800 United States School of Computer Science Georgia Institute of Technology AtlantaGA30332 United States Yale University New HavenCT06520 United States Center for Computational Sciences and Engineering Lawrence Berkeley National Lab BerkeleyCA94720 United States Department of Physics and Astronomy The University of Alabama TuscaloosaAL35487-0324 United States

The dimmest and most numerous outlier of the Type Ia supernova population, Type Iax events, is increasingly being found in the results of observational campaigns. There is currently no single accepted model to describe these events. This 2D study explores the viability of modeling Type Iax events as a hybrid C/O/Ne white dwarf progenitor undergoing a deflagration using the multi-physics software FLASH. This hybrid was created using the stellar evolution code MESA, and its C-depleted core and mixed structure have demonstrated lower yields than traditional C/O progenitors in previous deflagration-to-detonation studies. To generate a sample, 30 "realizations" of this simulation were performed, the only difference being the shape of the initial matchhead used to start the deflagration. As consistent with earlier work, these realizations produce the familiar hot dense bound remnant surrounded by sparse ejecta. Our results indicate the majority of the star remains unburned (∼ 70%) and bound (> 90%). Our realizations produce total ejecta yields on the order of 10−2 - 10−1 M☉, ejected 56Ni yields on the order of 10−4 - 10−2 M☉, and ejecta kinetic energies on the order of 1048 - 1049 ergs. Compared to yields inferred from recent observations of the dimmest Type Iax events - SN 2007qd, SN 2008ha, SN 2010ae, SN 2019gsc, SN 2019muj, SN 2020kyg, and SN 2021fcg - our simulation produces comparable 56Ni yields, but too-small total yields and kinetic energies. Reignition of the remnant is also seen in some realizations. © 2023, CC BY.

关键词： Supernovae

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Colour quantisation using self-organizing migrating algorithm 20

Colour quantisation using self-organizing migrating algorith...

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2020 Genetic and Evolutionary Computation Conference, GECCO 2020

作者： Mousavirad, Seyed Jalaleddin Schaefer, Gerald Korovin, Iakov Nature-inspired Computational Intelligence Lab Ontario Tech University Oshawa Canada Department of Computer Science Loughborough University Loughborough United Kingdom Souther Federal University Taganrog Russia

ISBN: (纸本)9781450371278

Colour quantisation is a common image processing technique to reduce the number of distinct colours in an image. Selecting these colour, which comprise a colour palette, is a challenging task since they determine the resulting image quality. In this paper, we propose a novel colour quantisation algorithm based on the Self-Organizing Migrating Algorithm (SOMA), in particular, SOMA Team To Team Adaptive (SOMA T3A), a recent variant of SOMA. SOMA T3A works, iteratively in three phases, namely organization, migration, and update, and performs adaptive parameter definition. Migrants are selected from the population and move towards a leader during the organization process. Experimental results on a benchmark set of images show excellent colour quantisation performance and our approach to outperform several conventional and soft-computing-based colour quantisation algorithms. © 2020 ACM.

关键词： Color

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Detecting negation cues and scopes in Spanish 12

Detecting negation cues and scopes in Spanish

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12th International Conference on Language Resources and Evaluation, LREC 2020

作者： Jiménez-Zafra, Salud María Morante, Roser Blanco, Eduardo Martín-Valdivia, María Teresa Alfonso Ureña-López, L. SINAI Computer Science Department CEATIC Universidad de Jaén Spain CLTL Lab Computational Linguistics VU University Amsterdam Netherlands University of North Texas United States

ISBN: (纸本)9791095546344

In this work we address the processing of negation in Spanish. We first present a machine learning system that processes negation in Spanish. Specifically, we focus on two tasks: i) negation cue detection and ii) scope identification. The corpus used in the experimental framework is the SFU ReviewSP-NEG. The results for cue detection outperform state-of-the-art results, whereas for scope detection this is the first system that performs the task for Spanish. Moreover, we provide a qualitative error analysis aimed at understanding the limitations of the system and showing which negation cues and scopes are straightforward to predict automatically, and which ones are challenging. © European Language Resources Association (ELRA), licensed under CC-BY-NC

关键词： Negation cues detection Negation processing Scope identification SFU ReviewSP-NEG corpus Spanish

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High-dimensional multi-level image thresholding using self-organizing migrating algorithm 20

High-dimensional multi-level image thresholding using self-o...

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2020 Genetic and Evolutionary Computation Conference, GECCO 2020

ISBN: (纸本)9781450371278

Multi-level image thresholding is a common approach to image segmentation for which population-based metaheuristic algorithms present an interesting alternative to conventional methods that are based on a exhaustive search. In this paper, we propose a novel multi-level image thresholding algorithm based on the Self-Organizing Migrating Algorithm (SOMA), in particular SOMA Team To Team Adaptive (SOMA T3A), a recent variant of SOMA, and an entropy-based fitness function. We evaluate our algorithm on a set of benchmark images on high-dimensional search spaces and with regards to fitness function value and peak signal-to-noise ratio (PSNR). Experimental results demonstrate excellent thresholding performance and our algorithm to outperform nine other state-of-the-art metaheuristics. © 2020 ACM.

关键词： Image segmentation

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Feature Interaction in Smart Environments

Research Square

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Research Square 2021年

作者： Jesus, Luis Emanuel Neves Claro, Daniela Barreiro Rios, Tatiane Nogueira FORMAS Research Group Computer Science Department Federal University of Bahia Institute of Mathematics BA Salvador Brazil CINO - Computational Intelligence and Optimization Research Lab Computer Science Department Federal University of Bahia Institute of Mathematics BA Salvador Brazil

The Internet of Things (IoT) connects many devices daily together in the same environment. Each device may follow the set of rules from a static environment. A static environment is usually controlled by an expert who knows all the necessary rules to provide this environment. The violation of one rule can cause a feature interaction. A feature interaction occurs when two or more devices generate instability in an environment. In a dynamic environment like IoT, devices’ inclusion, and exclusion make it impossible for an expert to maintain all these rules up-to-date. It is necessary to provide an automatic solution to avoid violating these rules and maintain the environment’s good performance. Thus, this work introduces a new approach to detect a feature interaction in dynamic environments automatically. Almost all previous work provide static rules defined by an expert in a controlled environment to detect an interaction. However, this is not possible in dynamic environments because of the number of device interactions and the number of device connections in/out, which grow exponentially in IoT environments. We started with a lightweight systematic review to better position our research, and then we identified one gap to provide our solution. Thus, our method learns to detect the interactions based on data analysis and then automatically predict the device detections in IoT environments. Datasets were manually annotated. Experiments were performed, and results provide evidence that automatic detection of a set of device interactions is possible in similar or either in complementary domains. © 2021, CC BY.

关键词： Internet of things

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A general framework for lifelong localization and mapping in changing environment

arXiv

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arXiv 2021年

作者： Zhao, Min Guo, Xin Song, Le Qin, Baoxing Shi, Xuesong Lee, Gim Hee Sun, Guanghui Gaussian Robotics Shanghai China Intel Labs China Beijing China Computer Vision and Robotic Perception Lab Department of Computer Science School of Computing National University of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology China

The environment of most real-world scenarios such as malls and supermarkets changes at all times. A prebuilt map that does not account for these changes becomes out-of-date easily. Therefore, it is necessary to have an up-todate model of the environment to facilitate long-term operation of a robot. To this end, this paper presents a general lifelong simultaneous localization and mapping (SLAM) framework. Our framework uses a multiple session map representation, and exploits an efficient map updating strategy that includes map building, pose graph refinement and sparsification. To mitigate the unbounded increase of memory usage, we propose a maptrimming method based on the Chow-Liu maximum-mutualinformation spanning tree. The proposed SLAM framework has been comprehensively validated by over a month of robot deployment in real supermarket environment. Furthermore, we release the dataset collected from the indoor and outdoor changing environment with the hope to accelerate lifelong SLAM research in the community. Our dataset is available at https://***/sanduan168/lifelong-SLAM-dataset. © 2021, CC BY.

关键词： Retail stores

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Robotic needle steering in deformable tissues with extreme learning machines

arXiv

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arXiv 2021年

作者： Perrusi, Pedro Henrique Suruagy Cazzaniga, Anna Baksic, Paul Tagliabue, Eleonora de Momi, Elena Courtecuisse, Hadrien Strasbourg France Electronic Information and Bioengineering Department Politecnico Di Milano Milan Italy Altair Robotics Lab Computer Science Departement University of Vernona Verone Italy

Control strategies for robotic needle steering in soft tissues must account for complex interactions between the needle and the tissue to achieve accurate needle tip positioning. Recent findings show faster robotic command rate can improve the control stability in realistic scenarios. This study proposes the use of Extreme Learning Machines to provide fast commands for robotic needle steering. A synthetic dataset based on the inverse finite element simulation control framework is used to train the model. Results show the model is capable to infer commands 66% faster than the inverse simulation and reaches acceptable precision even on previously unseen trajectories. Copyright © 2021, The Authors. All rights reserved.

关键词： Needles

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A Video-based Study on Perceived Intelligence, Subjective Performance and Trust under Variation of Prior Information given to Users in Autonomous Driving

A Video-based Study on Perceived Intelligence, Subjective Pe...

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IEEE Workshop on Advanced robotics and its Social Impacts, ARSO

作者： Kolja Kü hnlenz Ute Schmid Barbara Kü hnlenz Department of Electrical Engineering and Computer Science Robotics Research Lab Coburg University of Applied Sciences and Arts Coburg Germany Cognitive Systems Group University of Bamberg Bamberg Germany Academic Center for Sciences and Humanities Coburg University of Applied Sciences and Arts Coburg Germany

This paper presents results from a video-based study on the impact of prior information on the user experience dimensions perceived intelligence, subjective performance, and trust in autonomous driving. A simulated autonomous driving situation is presented to test participants, while they are given different prior information in terms of descriptions of the autonomous vehicle and its integration in a network of intelligent vehicles. Significant differences of the tested user experience dimensions are revealed underlining the importance of information provided to the potential users and towards the criticality of information regarding the introduction of intelligent technology in general.

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