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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Chuang Zhang Jialin Shi Wenxue Wang Ning Xi Yuechao Wang Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences 110016 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science 10016 China Emerging Technologies Institute Department of Industrial & Manufacturing Systems Engineering University of Hong Kong Pokfulam Hong Kong

ISBN: (纸本)9781509037636

Cellular mechanical properties as the main physical performance characteristics have been actively studied in the past years for the study of cytobiology and the development of medicine. In this study, by combining Hertz model, a novel strategy is proposed to simultaneously measure the cellular mechanical properties including cellular mass, elasticity and viscosity, based on the principle of forced vibration stimulated by simple harmonic force, with piezoelectric transducer (PZT) as vibrator and Atomic Force Microscope (AFM) as detector. The corresponding theoretical model was derived and the simulation was realized based on the proposed model. The experiments of indentations and vibrations with myoblasts and myotubes were implemented to calculate the three mechanical parameters of cells according to the proposed strategy. The results validated the proposed approach. This work would be useful for the development of cytology, medicine, previously diagnose, specific therapy and so on.

关键词： Vibrations Force Substrates Cells (biology) Force measurement

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Control laws development for a free-flying unmanned robotic system to support interplanetary bodies prospecting and characterization missions

Control laws development for a free-flying unmanned robotic ...

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AIAA Guidance, Navigation, and Control Conference, 2016

作者： Perez, Andres E. Moncayo, Hever Prazenica, Richard J. Zacny, Kris Mueller, Robert P. Ebert, Tom Dupuis, Michael Flight Dynamics and Control Research Laboratory Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Aerospace Engineering Department Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Exploration Technology Group Honneybee Robotics Company CA United States Exploration Research and Technology Programs Science and Technology Projects Division NASA Kennedy Space Center FL United States Autonomous Flight Systems Lead Testing and Design Branch NASA Kennedy Space Center FL United States Robotics and Autonomous Systems Testing and Design Branch NASA Kennedy Space Center FL United States

ISBN: (数字)9781624103896

ISBN: (纸本)9781624103896

In situ Resource Utilization (ISRU) facilitates planetary exploration by drawing needed resources, such as water, from the local environment. However, the extreme nature of these environments require the development of advanced unmanned space systems integrated with sample-capture devices to achieve the ultimate goal of prospecting these resources. This paper presents the design, development and Hardware-in-the-Loop (HIL) simulation testing of guidance and tracking control laws for an autonomous small marsupial free-flyer prospector system. The control laws are based on an extended non-linear dynamic inversion (NLDI) approach and its implementation is illustrated through HIL simulation using a mathematical model of an autonomous vehicle research platform developed by NASA Kennedy Space Center. This vehicle has been designed to support the development, testing and validation of algorithms for safe, reliable, and scalable control space missions with minimal need for human intervention in complex, unstructured environments. The main objective of the control laws is to minimize 3-axis distances with respect to a desired trajectory and maintain stability and adequate performance in the presence of uncertainties. The performance of the control laws is evaluated during autonomous flight in terms of trajectory tracking errors, real-time execution on board the flight computer, and control activity at nominal and dynamically-changing conditions. The results show that for all mission cases investigated the control laws approach has desirable capabilities and is reliable for in-flight testing operation as a next step towards the validation and verification of this configuration. © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hardware-in-the-loop simulation

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Electron beam introduced metallic nanowires growth

Electron beam introduced metallic nanowires growth

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IEEE Conference on Nanotechnology

作者： Zhichao Chen Zhan Yang Tao Chen Lining Sun Toshio Fukuda Laboratory of Advanced Robotics & Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou China school of mechatronics engineering Harbin Institute of Technology Harbin China Department of Micro-Nano Systems Engineering Nagoya University Nagoya Japan

This paper presented a method of growing metallic nanowires by using electron beam technology under scanning electron microscopy (SEM). The metallic nanoparticles were dispersed evenly on Indium-Tin Oxide (ITO) by the spin coater. The ITO sample was experimentally prepared by the spin coating technique. The electron beam was focused on a metallic nano particle inside SEM, which were dispersed on the ITO. The growth of metallic nanowires was controlled by the movement of the electron beam. The method this paper presented can be employed for different kinds of metallic and can be used to fabricate metallic nanowires with different length.

关键词： Nanowires Electron beams Nanoparticles Nanobioscience Nanoscale devices Copper Indium tin oxide

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Local perspectives of Plecoglossusaltivelis determine searching strategy

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AIP Conference Proceedings 2017年第1期1863卷

作者： Takayuki Niizato Hisashi Murakami Kazuki Sangu Takenori Tomaru Kohei Sonoda Yuta Nishiyama Yukio-Pegio Gunji 1Faculty of Engineering Information and Systems Tsukuba University Tsukuba Ibaraki Japan 2Faculity of Engineering Kanagawa University Yokohama Kanagawa Japan 3School of Fundamental Science and Engineering Waseda University Shinjuku Tokyo Japan 4Human Robotics Laboratory College of Information Science and Engineering Ritsumeikan University Japan 5Science & Technology Entrepreneurship Laboratory (e-Square) Osaka University Suita Osaka Japan

We argue for the notion of adaptability in collective behavior, treating real fish schools as an example. For evaluation, we use the inconsistent relation between local and global perspectives. We show that this incon...

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Study of adhesion force between cellulose micro-sphere and cellulose membrane

Study of adhesion force between cellulose micro-sphere and c...

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International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)

作者： Yuli Lai Pasi Kallio Hao Zhang Hui Xie Yasuhito Sugano Johan Bobacka Department of Automation Science and Engineering Tampere University of Technology Tampere Finland The State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Department of Chemistry University of Helsinki Helsinki Finland Johan Gadolin Process Chemistry Centre Åbo Akademi University Turku Finland

ISBN: (纸本)9781509029464

Development of novel high added value cellulose products requires improved understanding of interaction forces, which includes also the adhesion force, between cellulose surfaces. However, the interaction forces between cellulose surfaces have not been adequately studied. In this paper, cellulose-cellulose adhesion force is studied by using a customized dual-probe atomic force microscope (AFM) with a cellulose colloidal probe. Two different types of cellulose membranes (CM) with cellulose concentration of 1.5% and 2% are used as test samples, and about ten thousand tests are repeated on each CM sample type. Adhesion force histograms are provided and they show a large difference between the two types of CM. The average adhesion force on CM 1.5% is approximately 10 times higher than that on CM 2%. On CM 1.5%, the adhesion forces concentrate on the range from 450nN to 650nN, whereas on CM 2% the force distribute from 50 to 75nN. The difference in the adhesion force on these two types of CM can be attributed to their difference in surface roughness and surface energy.

关键词： Probes Adhesives Force Surface topography Force measurement Rough surfaces Surface roughness

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Cooperative formation control in the scope of the EC MORPH project: Theory and experiments

Cooperative formation control in the scope of the EC MORPH p...

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OCEANS - Europe

作者： Pedro Caldeira Abreu Mohammadreza Bayat João Botelho Pedro Góis João Gomes António Pascoal Jorge Ribeiro Miguel Ribeiro Manuel Rufino Luís Sebastião Henrique Silva Laboratory of Robotics and Systems in Engineering and Science (LARSyS) Universidade de Lisboa Lisboa Lisboa PT Laboratory of Robotics and Systems in Engineering and Science (LARSyS) University of Lisbon Lisbon Portugal

The EC MORPH project, described in [1], proposes a novel concept of an underwater robotic system that emerges from the integration, albeit in a non-physical manner, of several different mobile robot-modules with distinct and complementary resources. This approach aims to afford end-users efficient tools to map the underwater environment with great accuracy in situations that defy existing technology: namely, underwater surveys over rugged terrain and structures with full 3D complexity. The paper gives a brief presentation of theoretical and practical implementation issues on cooperative navigation and formation control, followed by a description of the results of tests carried out at sea with vehicles from different partners, in June and September 2014. The theoretical set-up builds on leader-follower formation control algorithms, whereby formation control is achieved in both relative position (using USBL units) and range-only measurement (using range measuring devices) scenarios. We conclude with the improvements introduced for the recent trials in Girona, March 2015, that will be the focus of work in the immediate future.

关键词： Vehicles Target tracking Acoustics Trajectory Sea measurements Oceans Robots

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Gesture recognition based on sparse representation

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International Journal of Wireless and Mobile Computing 2016年第4期11卷 348-356页

作者： Miao, Wei Li, Gongfa Sun, Ying Jiang, Guozhang Kong, Jianyi Liu, Honghai College of Machinery and Automation Wuhan University of Science and Technology Wuhan430081 China State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Intelligent Systems and Biomedical Robotics Group School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

Aiming at the problem that the robustness of gesture recognition is difficult to guarantee, this paper presents a method based on multi-features and sparse representation. Hu invariant moments and HOG features of training samples are extracted in training phase. The K-SVD algorithm is used to train the initial value of dictionary formed by two features so as to obtain two sub-dictionaries. In recognition phase, sparse coefficients of corresponding training dictionary are derived by solving minimum l1-norm. Finally, the overall reconstruction error is calculated to judge the categories of test samples. In experimental simulation, five kinds of grasp gesture are collected to create gesture sample library. After selecting optimal HOG parameters and the weight of two features, the recognition effect of the method is analysed. Compared with the commonly used classification, the results show that the method has better recognition rate and robustness. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Gesture recognition

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Cooperative Navigation and Control: the EU MORPH project

Cooperative Navigation and Control: the EU MORPH project

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Oceans MTS/IEEE Washington (Conference)

作者： Pedro Caldeira Abreu Mohammadreza Bayat Joao Botelho Pedro Gois Joao Pedro Gomes Antonio Pascoal Jorge Ribeiro Miguel Ribeiro Manuel Rufino Luis Sebastiao Henrique Silva Laboratory of Robotics and Systems in Engineering and Science (LARSyS) ISR/IST University of Lisbon

ISBN: (纸本)9781467393744

The EU MORPH project advances the use of a formation of five autonomous marine vehicles for mapping and scientific surveying of challenging, unstructured underwater environments as a means to overcome the limitations imposed by current single-vehicle based technology. We describe the test scenarios envisioned in the project and the requirements and constraints that they impose on the cooperative navigation and control systems that enable the concerted operation of the vehicle formation. We then provide a high-level description of each of the blocks that compose the final navigation and formation control architecture, developed at ISR/IST. We highlight how the systems take into account specific mission-related requirements and applications (e.g., typical trajectories employed for mapping and surveying). We describe the results of several trials at sea (involving multiple partners in the project and a group of heterogeneous vehicles) that illustrate the applicability of the MORPH concept in real operational scenarios as well as the limitations of the systems developed.

关键词： Autonomous marine vehicles Underwater surveying Formations of autonomous vehicles Cooperative navigation and control

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