首页期刊导航|Robotics & Machine Learning Daily News
期刊信息/Journal information
Robotics & Machine Learning Daily News
NewsRx
Robotics & Machine Learning Daily News

NewsRx

Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News
正式出版
收录年代

    Data on Robotics and Mechatronics Reported by a Researcher at Waseda University (Enhancing Multi-Agent Cooperation Through Action-Probability-Based Communicatio n)

    95-95页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on robotics and mechatroni cs is now available. According to newsoriginating from Tokyo, Japan, by NewsRx correspondents, research stated, “Although communicationplays a pivotal role in achieving coordinated activities in multi-agent systems, conventional approache soften involve complicated high-dimensional messages generated by deep networks .”

    Nanchang Institute of Technology Reports Findings in Robotics (Research on Gas-A ssisted Extrusion of Elastic Material Round-Tube for Flexible Robot Body)

    96-96页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Robotics is the subjec t of a report. According to news reporting outof Jiangxi, People’s Republic of China, by NewsRx editors, research stated, “The flexible robot is widelyused in a variety of fields such as medical treatment, rescue and disaster relief, indu stry, and agriculture.Using elastic materials to prepare flexible robot body st ructures is the core of the study of flexible robots.”Funders for this research include Nanchang Institute of Technology, Education De partment of JiangxiProvince, National Natural Science Foundation of China, Natu ral Science Foundation of Jiangxi Province,Teaching Reform Program of Jiangxi C olleges and Universities.

    First Affiliated Hospital of Dalian Medical University Reports Findings in Bioma rkers (A more objective PD diagnostic model: integrating texture feature markers of cerebellar gray matter and white matter through machine learning)

    97-97页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Diagnostics and Screen ing - Biomarkers is the subject of a report.According to news reporting origina ting in Dalian, People’s Republic of China, by NewsRx journalists,research stat ed, “The purpose of this study is to explore whether machine learning can be use d to establishan effective model for the diagnosis of Parkinson’s disease (PD) by using texture features extracted fromcerebellar gray matter and white matter , so as to identify subtle changes that cannot be observed by thenaked eye. Thi s study involved a data collection period from June 2010 to March 2023, includin g 374subjects from two cohorts.”

    Italian Institute of Technology Reports Findings in Androids (When performing ac tions with robots, attribution of intentionality affects the sense of joint agen cy)

    98-98页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Robotics - Androids is the subject of a report. According to newsreporting originating in Genova, Ita ly, by NewsRx journalists, research stated, “Sense of joint agency(SoJA) is the sense of control experienced by humans when acting with others to bring about c hanges inthe shared environment. SoJA is proposed to arise from the sensorimoto r predictive processes underlyingaction control and monitoring.”

    Study Results from Harbin Institute of Technology in the Area of Androids Report ed (Learning Responsive Humanoid Motion Skills From Graph-powered Motion Matchin g)

    99-99页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ro botics - Androids. According to news reportingoriginating from Harbin, People’s Republic of China, by NewsRx correspondents, research stated, “Toachieve robot motion imitating, it is important to ensure morphological similarity, physical feasibility, andgeneralization of actions between robots and motion capture dat asets. Traditional motion controllersrequire designing controllers for each mot ion type, which can be time-consuming to adjust controllerparameters.”

    Fritz Haber Institute of the Max-Planck Society Reports Findings in Machine Lear ning (Revealing the structure of the active sites for the electrocatalytic CO2 r eduction to CO over Co single atom catalysts using operando XANES and machine .. .)

    100-100页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Berlin, Germany, by News Rx journalists, research stated, “Transition-metal nitrogen-dopedcarbons (TM-N- C) are emerging as a highly promising catalyst class for several important elect rocatalyticprocesses, including the electrocatalytic CO reduction reaction (COR R). The unique local environmentaround the singly dispersed metal site in TM-N- C catalysts is likely to be responsible for their catalyticproperties, which di ffer significantly from those of bulk or nanostructured catalysts.”

    University of Bordeaux Reports Findings in Artificial Intelligence (The beating heart: artificial intelligence for cardiovascular application in the clinic)

    101-101页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Artificial Intelligenc e is the subject of a report. According tonews reporting from Pessac, France, b y NewsRx journalists, research stated, “Artificial intelligence (AI)integration in cardiac magnetic resonance imaging presents new and exciting avenues for adv ancing patientcare, automating post-processing tasks, and enhancing diagnostic precision and outcomes. The use of AIsignificantly streamlines the examination workflow through the reduction of acquisition and postprocessingdurations, coup led with the automation of scan planning and acquisition parameters selection.”

    Bursa Technical University Researchers Publish Findings in Robotics (Task planni ng and formal control of robotic assembly systems: A Petri net-based approach)

    102-102页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on robotics are presented i n a new report. According to news originating fromBursa Technical University by NewsRx correspondents, research stated, “In modern industrial production,robot ic assembly systems play a crucial role. As robots take on more tasks, the need for formal methodsarises to define, control, and execute these tasks.”

    Study Findings on Machine Learning Are Outlined in Reports from Technical Univer sity Berlin (TU Berlin) (Image Processing and Machine Learning for Hyperspectral Unmixing: an Overview and the Hysupp Python Package)

    102-103页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingfrom Berlin, Germany, by NewsRx jo urnalists, research stated, “Spectral pixels are often a mixture of the pure spe ctra of the materials, called endmembers, due to the low spatial resolution of h yperspectralsensors, double scattering, and intimate mixtures of materials in t he scenes. Unmixing estimates thefractional abundances of the endmembers within the pixel.”

    New Findings from Beijing Jiaotong University Update Understanding of Machine Le arning (Knee-point-conscious Battery Aging Trajectory Prediction Based On Physic s-guided Machine Learning)

    103-104页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingoriginating from Beijing, People’s R epublic of China, by NewsRx correspondents, research stated, “Earlyprediction o f aging trajectories of lithium-ion (Li-ion) batteries is critical for cycle lif e testing, qualitycontrol, and battery health management. Although data-driven machine learning (ML) approaches arewell suited for this task, unfortunately, r elying solely on data is exceedingly time-consuming and resourceintensive,even in accelerated aging with complex aging mechanisms.”