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Instance segmentation based recognition system tracking tomatoes by ripeness in natural light conditions

Journal of Institute of Control, robotics and Systems 2020年第11期26卷 940-948页

作者： Lee, Woo-Young Ko, Kwang Eun Kang, Jaehyeon Park, Hyun Ji Jang, Inhoon Applied Robot R&D Department Korea Institute of Industrial Technology Korea Republic of Department of computer Science & Engineering Hanyang University Korea Republic of

This paper describes a tomato recognition system to be applied to a harvesting robot used in farms under natural light conditions. The tomato recognition system is composed of a stereo camera, light, deep learning based instance segmentation model and Kalman filter based object tracking algorithm. In order to train the instance segmentation model, a large-scale dataset of the actual smartfarm background is made, and performance verification is performed on the test dataset. The average precision of the deep learning based instance segmentation model achieved 96.8% of performance when the threshold of the prediction score for classifying ripeness is over 0.75 (Table. 3), and the multiple object tracking accuracy of the Kalman filter based tracking method is approximately 74.3%. © ICrOS 2020.

关键词： Kalman filters

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Cosmic-ray acceleration and escape from supernova remnant W44 as probed by Fermi-LAT and MAGIC

arXiv

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arXiv 2025年

作者： Abe, S. Abhir, J. Abhishek, A. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Asano, K. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Bautista, A. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bonnoli, G. Bošnjak, Ž. Bronzini, E. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, r. Carretero-Castrillo, M. Castro-Tirado, A.J. Cerasole, d. Ceribella, G. Chai, Y. Chilingarian, A. Cifuentes, A. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. d'Amico, G. d'Elia, V. da Vela, P. dazzi, F. de Angelis, A. de Lotto, B. de Menezes, r. del Popolo, A. delfino, M. delgado, J. delgado Mendez, C. di Pierro, F. dominis Prester, d. donini, A. dorner, d. doro, M. Elsaesser, d. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukazawa, Y. García López, r.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Gliwny, P. Godinović, N. Gozzini, S.r. Gradetzke, T. Grau, r. Green, J.G. Günther, P. Hadasch, d. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, d. Hütten, M. Imazawa, r. Ishio, K. Jiménez Martínez, I. Jormanainen, J. Kayanoki, T. Kerszberg, d. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez, M. Lamastra, A. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, r. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, d. Menchiari, S. Mender, S. Miceli, d. Miener, T. Miranda, J.M. Mirzoyan, r. Molero González, M. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, d. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Nickel, L. Nievas rosillo, M. Nigro, C. Nikolić, L. Nishijima, K. Njoh Ekoume, T. The University of Tokyo Chiba Kashiwa277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Università di Siena INFN Pisa SienaI-53100 Italy Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik GarchingD-85748 Germany Università di Padova INFN PadovaI-35131 Italy Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain 22290-180 URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Bellaterra BarcelonaE-08193 Spain Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy Croatian MAGIC Group University of Rijeka Faculty of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany Technische Universität Dortmund DortmundD-44221 Germany University of Geneva Chemin d'Ecogia 16 VersoixCH-1290 Switzerland Japanese MAGIC Group: Physics Program Graduate School of Advanced Science and Engin

Context. The supernova remnant (SNr) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (Crs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy Crs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNr and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100 MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. results. The combined spectra of Fermi-LAT and MAGIC, extending from 100 MeV to several TeV, were used to derive constraints on the escape of Crs. Using a time-dependent model to describe the particle acceleration and escape from the SNr, we show that the maximum energy of the accelerated particles has to be 40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission. Copyright © 2025, The Authors. All rights reserved.

关键词： Cosmic rays

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An aptamer-based shear horizontal surface acoustic wave biosensor with a CVd-grown single- layered graphene film for high-sensitivity detection of a label-free endotoxin

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Microsystems & Nanoengineering 2020年第1期6卷 1247-1257页

作者： Junwang Ji Yiquan Pang dongxiao Li Zheng Huang Zuwei Zhang Ning Xue Yi Xu Xiaojing Mu Key Laboratory of Optoelectronic Technology&Systems Ministry of EducationInternational R&D Center of Micro-nano Systems and New Materials TechnologyChongqing University400044 ChongqingChina School of Chemistry and Chemical Engineering Chongqing University400030 ChongqingChina Department of Applied Physics Chongqing University401331 ChongqingChina Chongqing Acoustic-Optic-Electric Corporation China Electronic Technology Group Corporation400060 ChongqingChina Institute of Electronics Chinese Academy of Sciences100190 BeijingChina

The thickness of the sensitive layer has an important influence on the sensitivity of a shear horizontal surface acoustic wave(SH-SAW)biosensor with a delay-line structure and lower layer numbers of graphene produce better sensitivity for biological ***,a label-free and highly sensitive SH-SAW biosensor with chemical vapor deposition(CVd-)-grown single-layered graphene(SLG)for endotoxin detection was developed in this *** this methodology,SH-SAW biosensors were fabricated on a 36°Y-90°X quartz substrate with a base frequency of 246.2MHz,and an effective detection cell was fabricated using acrylic *** increase the surface hydrophilicity,chitosan was applied to the surface of the SLG ***,the aptamer was immobilized on the surface of the SLG film by cross-linking with ***,the sensitivity was verified by endotoxin detection with a linear detection ranging from 0 to 100 ng/mL,and the detection limit(LOd)was as low as 3.53 ng/*** addition,the stability of this type of SH-SAW biosensor from the air phase to the liquid phase proved to be excellent and the specificity was tested and verified by detecting the endotoxin obtained from Escherichia coli(***),the endotoxin obtained from Pseudomonas aeruginosa(***),and ***,this type of SH-SAW biosensor with a CVd-grown SLG film may offer a promising approach to endotoxin detection,and it may have great potential in clinical applications.

关键词： film surface layered

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reinforcement Learning Based Position Control of 1-dOF rotational Hydraulic Actuator

Reinforcement Learning Based Position Control of 1-DOF Rotat...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Hokwon Kang Jin Tak Kim Sangsin Park Jungsan Cho Department of Robotics Engineering University of Science and Technology(UST) Daejeon Korea The Hydraulic Robot Laboratory Robot R&D Group Korea Institute of Industrial Technology(KITECH) Ansan South Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In this study, we propose a reinforcement learning (rL) based position control method for a one-degree-of-freedom (1-dOF) rotational hydraulic actuator. Controlling hydraulic actuators is challenging due to their nonlinear characteristics and complex structure. reinforcement learning offers the advantage of enabling control through learning without requiring a detailed understanding of the model, using virtual environments. However, simulators do not perfectly replicate real-world conditions. To address this, we aim to enhance the fidelity of the simulation and improve the performance of reinforcement learning-based controllers by integrating real-world data into the simulation using deep neural networks (dNN). The reinforcement learning is trained using the Proximal Policy Optimization (PPO) algorithm, and it is validated through experiments with step and sine inputs.

关键词： Legged locomotion refining Hydraulic actuators Position control Virtual environments reinforcement learning Artificial neural networks Hydraulic systems Control systems Optimization

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Graphene oxide MgFe2O4 nanocomposites for Cr(VI) remediation: a comparative modeling study

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Nanotechnology for Environmental Engineering 2018年第1期3卷 1-11页

作者： Hosseini, Seyed Ali Talebipour, Sahar Neyestani, Mahmoud reza ranjan, Shivendu dasgupta, Nandita Department of Applied Chemistry Faculty of Chemistry Urmia University Urmia Iran Department of Chemistry Faculty of Science Zanjan University Zanjan Iran R&D and Technology Development E-Spin Nanotech Pvt Ltd SIDBI Incubation Center IIT Kanpur KanpurUttar Pradesh208016 India Nano-food Research Group School of Bio Sciences and Technology VIT University VelloreTamil Nadu India

The article describes the synthesis and application of magnesium ferrite nanoparticles (MgFe2O4 NPs) and engineered MgFe2O4 nanocomposites (NCs) by graphene oxide as green and easy separable magnetic adsorbents in removal of Cr(VI) from environmental pollutant. The statistical study of the adsorption process and optimization was accomplished with central composite design method of response surface methodology (rSM) approach. The optimum conditions, predicted by rSM, were achieved at pH, contact time, initial Cr(VI) concentration and adsorbent dosage of 2, 60 min, 40 mg L−1 and 0.15 g, respectively. The removal of Cr(VI) under optimum situations was 97%, and the achieved result in practice was found to be 99%. Pareto analysis suggests the importance relative order of the factors as: pH > concentration of Cr(VI) > time > adsorbent dosage under optimized situations. The engineered nanocomposite was further analyzed for real groundwater samples, and 92% Cr(VI) remediation was resulted. The study is the first study for efficient Cr(VI) remediation from real groundwater sample using novel engineered nanocomposites and has potential to have societal as well as industrial impact in the form of process or product development. © 2018, Springer International Publishing AG, part of Springer Nature.

关键词： Nanocomposites

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Self-Supervised Button recognition for Indoor Mobile robots

Self-Supervised Button Recognition for Indoor Mobile Robots

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Jeong-Won Pyo Kwang-Hee Lee Jung-San Cho Tae-Yong Kuc Electrical and Computer Engineering SungKyunKwan University Suwon Korea Robot R&D Group Korea Institute of Industrial Technology Ansan korea

In recent years, with the rapid advances in technology, the precision and accuracy of indoor autonomous driving have also improved remarkably. However, despite the development of these technologies, there are still many difficulties to perform services through real mobile robots. In this paper, we focused on the mobile robot that drives in multiple spaces in a multi-story building using an elevator. In order to operate the elevator, the mobile robot must be able to operate by pressing the elevator button itself. To solve this problem, in this paper, we propose self-supervised button recognition. We created fake buttons for self-supervised learning and placed these on random backgrounds to increase the diversity of the dataset. In addition, the generated realistic buttons are re-generated like real buttons through a GAN. In experiments, we presented that our self-supervised button recognition was performed in an actual environment without separate labeling.

关键词： Training Self-supervised learning Pressing Generative adversarial networks Elevators Mobile robots Labeling

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Metaproteomics in the One Health framework for unraveling microbial effectors in microbiomes

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Microbiome 2025年第1期13卷 1-21页

作者： Heyer, robert Wolf, Maximilian Benndorf, dirk Uzzau, Sergio Seifert, Jana Grenga, Lucia Pabst, Martin Schmitt, Heike Mesuere, Bart Van den Bossche, Tim Haange, Sven-Bastiaan Jehmlich, Nico di Luca, Mariagrazia Ferrer, Manuel Serrano-Villar, Sergio Armengaud, Jean Bode, Helge B. Hellwig, Patrick Masselot, Catherine robbe Léonard, renaud Wilmes, Paul Multidimensional Omics Analyses Group Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Multidimensional Omics Analyses Group Faculty of Technology Bielefeld University Bielefeld Germany Bioprocess Engineering Otto-Von-Guericke University Magdeburg Magdeburg Germany Bioprocess Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Magdeburg Germany Applied Biosciences and Process Engineering Anhalt University of Applied Sciences Köthen Germany Department of Biomedical Sciences University of Sassari Sassari Italy Institute of Animal Science University of Hohenheim Stuttgart Germany HoLMiR - Hohenheim Center for Livestock Microbiome Research University of Hohenheim Stuttgart Germany Département Médicaments Et Technologies Pour La Santé (DMTS) Université Paris-Saclay CEA INRAE SPI Bagnols-Sur-Cèze France Department of Biotechnology Delft University of Technology Delft The Netherlands Institute for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium VIB - UGent Center for Medical Biotechnology VIB Ghent Belgium Department of Biomolecular Medicine Faculty of Medicine and Health Sciences Ghent University Ghent Belgium Department of Molecular Toxicology Helmholtz-Centre for Environmental Research - UFZ GmbH Leipzig Germany Department of Biology University of Pisa Pisa Italy Instituto de Catalisis y Petroleoquimica (ICP) CSIC Madrid Spain Department of Infectious Diseases Hospital Universitario Ramon y Cajal Instituto de Investigación Sanitaria Ramón y Cajal (IRYCIS) CIBER de Enfermedades Infecciosas Madrid Spain Department of Natural Products in Organismic Interactions Max-Planck-Institut for Terrestrial Microbiology Marburg Germany Center for Synthetic Microbiology (SYNMIKRO) Phillips University Marburg Marburg Germany Department of Ch

One Health seeks to integrate and balance the health of humans, animals, and environmental systems, which are intricately linked through microbiomes. These microbial communities exchange microbes and genes, influencing not only human and animal health but also key environmental, agricultural, and biotechnological processes. Preventing the emergence of pathogens as well as monitoring and controlling the composition of microbiomes through microbial effectors including virulence factors, toxins, antibiotics, non-ribosomal peptides, and viruses holds transformative potential. However, the mechanisms by which these microbial effectors shape microbiomes and their broader functional consequences for host and ecosystem health remain poorly understood. Metaproteomics offers a novel methodological framework as it provides insights into microbial dynamics by quantifying microbial biomass composition, metabolic functions, and detecting effectors like viruses, antimicrobial resistance proteins, and non-ribosomal peptides. Here, we highlight the potential of metaproteomics in elucidating microbial effectors and their impact on microbiomes and discuss their potential for modulating microbiomes to foster desired functions. Word Cloud showing the abundance of keywords in combination with the “Microbiome” in PubMed NCBI. As abundance values, the rounded logarithm with the base of 2 hits were used and submitted to https://***/create . For microbiome, the number without any combination was used for calculation. The word cloud displays different aspects of microbiome research: (i.) sources of microbiomes (green), (ii.) interactions (purple), (iii.) involved taxa (red), (iv.) applied experimental approaches (blue), and (vi.) societal effects and recent or future applications (gray).

关键词： Metaproteomics Microbial community Bacteriophages Microbiome Microbial effectors

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Quantifying the effect of noise, vibration and motion on human performance in ship collision and grounding risk assessment 12

Quantifying the effect of noise, vibration and motion on hum...

引用

12th International Probabilistic Safety Assessment and Management Conference, PSAM 2014

作者： Montewka, Jakub Goerlandt, Floris Innes-Jones, Gemma Owen, douglas Hifi, Yasmine Porthin, Markus Aalto University Department of Applied Mechanics Marine Technology Research Group on Maritime Risk and Safety Espoo Finland EMEA Bristol United Kingdom Brookes Bell R and D Glasgow United Kingdom VTT Technical Research Centre of Finland Espoo Finland

risk-based design (rBd) methodology for ships is a relatively new and a fast developing discipline. However, quantification of human error contribution to the risk of collision or grounding within rBd has not been considered before. This paper introduces probabilistic models linking the effect of ship motion, vibration and noise with risk through the mediating agent of a crewmember. The models utilize the concept of Attention Management, which combines the theories described by dynamic Adaptability Model, Cognitive Control Model and Malleable Attentional resources Theory. To model the risk, an uncertainty-based approach is taken, under which the available background knowledge is systematically translated into a coherent network and the evidential uncertainty is qualitatively assessed. The obtained results are promising as the models are responsive to changes in the GdF nodes as expected. The models may be used as intended by naval architects and vessel designers, to facilitate risk-based ship design.

关键词： Bayesian networks

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A new calibration method and experimental study for kinematic parameters of industrial robot

A new calibration method and experimental study for kinemati...

引用

2020 International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020

作者： Zhao, Honghua Zhao, Jian Lin, Yifei Han, Qifei Chen, Mianpeng University of Jinan School of Mechanical Engineering Jinan China Shandong University School of Control Science and Engineering Jinan China Shandong Institute of Intelligent Robot and Applied Technology Jining China GSK CNC Equipment Co. Ltd. CNC System R and D Department Guangzhou China

ISBN: (纸本)9781728182889

The accuracy of industrial robot kinematics parameters directly affects its absolute positioning accuracy. Based on Modify denavit-Hartenberg (Md-H) kinematics theory, a more accurate calibration method for kinematic parameters of industrial robots is proposed in this paper. It takes the kinematics parameters, deceleration ratio and coupling coefficient of the robot as error parameters to establish the error model. The calibration experiment and accuracy verification experiment are designed by laser tracker. After the introduction of the reduction ratio and the coupling coefficient calibration, the absolute positioning error of the robot in all directions has been greatly improved, and the overall average accuracy of the robot is increased by 91.42% compared with the uncalibrated, and is increased by 81.02% compared with the without introducing the deceleration ratio and coupling coefficient. © 2020 IEEE.

关键词： Kinematics

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Timing and noise analysis of five millisecond pulsars observed with MeerKAT

arXiv

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arXiv 2025年

作者： Chisabi, M. Andrianomena, S. Enwelum, U. Gasennelwe, E.G. Idris, A. Idogbe, E.A. Shilunga, S. Geyer, M. reardon, d.J. Okany, C.F. Shamohammadi, M. Shannon, r.M. Krishnan, V. Venkatraman Abbate, F. Kramer, M. Department of Physics & Astronomy University of Nigeria Nsukka410101 Nigeria Department of Physics The Copperbelt University Jambo Drive Kitwe21696 Zambia SARAO Liesbeek House River Park Liesbeek Parkway Settlers Way Cape Town7705 South Africa Department of Physics & Astronomy University of the Western Cape Cape Town7535 South Africa Department of Science Laboratory Technology University of Nigeria Nsukka Nigeria Department of Physics University of Botswana Gaborone Botswana National Space Research and Development Agency Centre for Basic Space Science Nsukka410102 Nigeria Department of Physics Chemistry and Material Science University of Namibia Private Bag 13301 Windhoek Namibia Group Department of Mathematics and Applied Mathematics University of Cape Town Rondebosch7701 South Africa Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Australia Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany INAF - Osservatorio Astronomico di Cagliari Via della Scienza 5 SelargiusI-09047 Italy

Millisecond pulsars (MSPs) in binary systems are precise laboratories for tests of gravity and the physics of dense matter. Their orbits can show relativistic effects that provide a measurement of the neutron star mass and the pulsars are included in timing array experiments that search for gravitational waves. Neutron star mass measurements are key to eventually solving the neutron star equation of state and these can be obtained by a measure of the Shapiro delay if the orbit is viewed near edge-on. Here we report on the timing and noise analysis of five MSPs observed with the MeerKAT radio telescope: PSrs J0900−3144, J0921−5202, J1216−6410, J1327−0755 and J1543−5149. We searched for the Shapiro delay in all of the pulsars and obtain weak detections for PSrs J0900−3144, J1216−6410, and J1327−0755. We report a higher significance detection of the Shapiro delay for PSr J1543−5149, giving a precise pulsar mass of Mp = 1.349+−00043061 M☉ and companion white-dwarf mass Mc = 0.223+−00005007 M☉. This is an atypically low mass measurement for a recycled MSP. In addition to these Shapiro delays, we also obtain timing model parameters including proper motions and parallax constraints for most of the pulsars. Copyright © 2025, The Authors. All rights reserved.

关键词： White dwarfs

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