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    New Robotics Study Findings Reported from School of Information Science and Tech nology (Integrated Modular Neural Control for Versatile Locomotion and Object Tr ansportation of a Dung Beetlelike Robot)

    29-29页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news reporting originating from Rayong, Thailand, by News Rx correspondents, research stated, “Dung beetles can effectively transport dung pallets of various sizes in any direction across uneven terrain. While this imp ressive ability can inspire new locomotion and object transportation solutions i n multilegged (insect-like) robots, to date, most existing robots use their legs primarily to perform locomotion.”

    Data on Robotics and Automation Reported by Researchers at Beihang University (A n Ultralight Air-ground Vehicle Capable of Sustained Amphibious Maneuverability and Bio-inspired Modality Transition)

    30-30页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics - Robotics and Automation is now available. According to news reporting originating from Beiji ng, People’s Republic of China, by NewsRx correspondents, research stated, “This letter presents a 5.2g ultra-lightweight air-ground vehicle capable of passive stable flying and terrestrial cruising. Such a design proposes a passive stabili ty layout, including a single-axis rotor, film dampers, and a stabilizer bar.”

    Findings from University of St Andrews Provide New Insights into Machine Learnin g (Pipar: : Pipeline Parallelism for Collaborative Machine Learning)

    31-31页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from St. Andrews, United Kingdom, by NewsRx correspondents, research stated, “Collaborative machine learn ing (CML) techniques, such as federated learning, have been proposed to train de ep learning models across multiple mobile devices and a server. CML techniques a re privacy-preserving as a local model that is trained on each device instead of the raw data from the device is shared with the server.” Financial support for this research came from Rakuten Mobile, Inc., Japan.

    Studies from Jiangnan University in the Area of Robotics and Automation Reported (Design of a Dual-layer Four Quadrants Orthogonal Microcoil Platform for Indepe ndent Control of Multiple Magnetic Microrobots)

    32-32页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics - Robotics a nd Automation have been presented. According to news reporting out of Wuxi, Peop le’s Republic of China, by NewsRx editors, research stated, “Compared to the lim itations of relying solely on a global magnetic field response, utilizing local magnetic fields enables the independent control of multiple microrobots, regardl ess of variations in their size and orientation. In this letter, we develop a du al-layer orthogonal local magnetic field generation system, by dividing the work place into four quadrants and setting transition microcoils between them.”

    New Machine Learning Findings from University of Illinois Outlined (Sensor Place ment Optimization In Sewer Networks: Machine Learning-based Source Identificatio n Approach)

    33-33页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in Chicago, Illi nois, by NewsRx journalists, research stated, “Wastewater surveillance has recen tly emerged as a valuable tool for environmental and public health monitoring. B y analyzing the constituents and biomarkers present in wastewater, stakeholders can gather critical information regarding contamination events and disease outbr eaks.”

    Studies from Beijing Normal University Add New Findings in the Area of Machine L earning (A Machine Learning Downscaling Framework Based On a Physically Constrai ned Sliding Window Technique for Improving Resolution of Global Water Storage An omaly)

    34-35页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting from Beijing, People’s Repub lic of China, by NewsRx journalists, research stated, “Terrestrial water storage anomaly (TWSA) and groundwater storage anomaly (GWSA) data are of great importa nce for hydrological research and water resource management. However, products d erived from the Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On mission (GRACE-FO) are constrained by the satellite design and variati on in processing strategies among different institutions, resulting in multiple suboptimal products.”

    New Findings from University of Perugia Describe Advances in Machine Learning (E nhancing Machine Learning Thermobarometry for Clinopyroxene-bearing Magmas)

    35-36页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news originating from Perugia, Italy, by NewsRx co rrespondents, research stated, “In this study, we proposed a general workflow th at aims to enhance the ML-based geothermobarometer modelling. Our workflow focus es on three key areas.” Funders for this research include Ministry of Education, Universities and Resear ch (MIUR), Swiss National Science Foundation (SNSF), European Research Council ( ERC), Ministry of Education, Universities and Research (MIUR), Swiss National Sc ience Foundation (SNSF).

    Investigators from Wuhan University Target Robotics (Robust Capsule-robot Positi oning With Limited Magnetic Observations: an Inertial-enhanced Approach)

    36-37页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Robotic s. According to news originating from Wuhan, People’s Republic of China, by News Rx correspondents, research stated, “The capsule robot has become an important t ool in covering the entire spectrum of digestive tract disease diagnosis. To ach ieve magnetic capsule-robot localization, the Levenberg-Marquardt (LM) algorithm has become a mainstream approach that provides accurate solutions in the genera l case.”

    Researcher at Huazhong University of Science and Technology Zeroes in on Robotic s (Adaptive Fault-Tolerant Control of Mobile Robots with Fractional-Order Expone ntial Super-Twisting Sliding Mode)

    37-38页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news originating from Wuhan, People’s Republic of China, by News Rx editors, the research stated, “Industrial mobile robots easily experience act uator loss of some effectiveness and additive bias faults due to the working sce narios, resulting in unexpected performance degradation.” Financial supporters for this research include National Natural Science Foundati on of China; China Postdoctoral Science Foundation; Guangdong Basic And Applied Basic Research Foundation.

    Researchers from Swinburne University of Technology Describe Findings in Machine Learning (Enhancing Road Safety With Machine Learning: Current Advances and Fut ure Directions In Accident Prediction Using Non-visual Data)

    38-39页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating in Sarawak, Malaysia, by New sRx journalists, research stated, “Road traffic accident (RTA) poses a significa nt road safety issue due to the increased fatalities worldwide. To address it, v arious artificial intelligence solutions are developed to analyze RTA characteri stics and make predictions.” Financial support for this research came from Swinburne HDR Scholarship.