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    Research from Beijing Information Science & Technology University Has Provided New Data on Robotics (Industrial Robot Trajectory Optimization Base d on Improved Sparrow Search Algorithm)

    87-88页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators publish new report on robotics. Acc ording to news originating from Beijing, People’sRepublic of China, by NewsRx e ditors, the research stated, “This paper proposes an enhanced multistrategyspa rrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressingissues of low efficiency and high vibration impact on joints during operation.”Funders for this research include Young Backbone Teacher Support Plan of The Bei jing InformationScience And Technology University; General Program of The Natio nal Natural Science Foundation ofChina.

    Data on Machine Learning Detailed by Researchers at Shaanxi University of Scienc e and Technology (Machine Learning-assisted Thermomechanical Coupling Fabrication of Hard Carbon for Sodium-ion Batteries)

    88-88页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsoriginating from Shaanxi, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Thisstudy conducts an extensive investigation into the application of hard carbon in sodium-ion bat teries.More than 100 hard carbon samples are meticulously synthesized by precis ely controlling temperature andpressure, and their microstructure and performan ce are comprehensively evaluated.”

    University of Surrey Reports Findings in Agricultural Robots (Optimising Robotic Operation Speed With Edge Computing Via 5g Network: Insights From Selective Har vesting Robots)

    89-90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 Agriculture - Agricultural Robots. According tonews reporting originating from Guildford, United Kingdom, by NewsRx correspondents, research stated,“Selective harvesting by autonomous robots will be a critical enabling technology for futu re farming.Increases in inflation and shortages of skilled labor are driving fa ctors that can help encourage useracceptability of robotic harvesting.”

    Changsha University of Science and Technology Researcher Provides New Study Find ings on Machine Learning (Binary Encoding-Based Federated Learning for Traffic S ign Recognition in Autonomous Driving)

    90-90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 artificial intelligence. According to news reportingfrom Changsha, People’s Rep ublic of China, by NewsRx journalists, research stated, “Autonomous drivinginvo lves collaborative data sensing and traffic sign recognition. Emerging artificia l intelligence technologyhas brought tremendous advances to vehicular networks. ”

    New Machine Learning Study Findings Have Been Reported from Slovak University of Technology Bratislava (Is Mouse Dynamics Information Credible for User Behavior Research? An Empirical Investigation)

    91-92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 reportingoriginating from Bratislava, Slova kia, by NewsRx correspondents, research stated, “Mouse dynamics, information on user’s interaction with a computer mouse, are in vogue in machine learning for p urposessuch as recommendations, personalization, prediction of user characteris tics and behavioral biometrics.We point out a blind spot in current works invol ving mouse dynamics that originates in underestimatingthe gravity of the charac teristics of the mouse device and configuration on the data that mouse dynamicsare inferred from.”

    Research Conducted at Czech Technical University Has Updated Our Knowledge about Robotics and Automation (Movingcables: Moving Cable Segmentation Method and Dat aset)

    91-91页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Robotics - Roboti cs and Automation are discussed in a newreport. According to news reporting out of Prague, Czech Republic, by NewsRx editors, research stated,“Manipulating cl uttered cables, hoses or ropes is challenging for both robots and humans. Humansoften simplify these perceptually challenging tasks by pulling or pushing tangl ed cables and observing theresulting motions.”Financial supporters for this research include European Union (EU), TACR.

    Findings from Zhengzhou University Has Provided New Data on Artificial Intellige nce (Bibliometric Analysis of Artificial Intelligence In Wastewater Treatment: C urrent Status, Research Progress, and Future Prospects)

    92-93页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Artificial In telligence have been published. According to newsreporting out of Zhengzhou, Pe ople’s Republic of China, by NewsRx editors, research stated, “Wastewatertreatm ent is an important topic for improving water quality and environmental protecti on, and artificialintelligence has become a powerful tool for wastewater treatm ent. This work provides research progressand a literature review of artificial intelligence applied to wastewater treatment based on the visualizationof bibli ometric tools.”

    Jiangsu University of Science and Technology Researcher Publishes Findings in Ma chine Learning (Machine-Learning-Based Characterization and Inverse Design of Me tamaterials)

    93-94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 ar tificial intelligence. According to news originatingfrom Zhenjiang, People’s Re public of China, by NewsRx correspondents, research stated, “Metamaterials,char acterized by unique structures, exhibit exceptional properties applicable across various domains.Traditional methods like experiments and finite-element method s (FEM) have been extensively utilized tocharacterize these properties.”

    Researchers at Beijing University of Technology Have Reported New Data on Machin e Learning [Machine Learning for Requirements Engineering (Ml 4re): a Systematic Literature Review Complemented By Practitioners’ Voices From Stack Overflow]

    94-95页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting out of Beijing, People’s Re public of China, by NewsRx editors, the research stated, “The researchof machin e learning for requirements engineering (ML4RE) has attracted more and more atte ntion fromresearchers and practitioners. Although pioneering research has shown the potential of using ML techniquesto improve RE practices, there lacks a sys tematic and comprehensive literature review in academia thatintegrates an indus trial perspective.”

    Studies from Chinese Academy of Sciences Yield New Data on Robotics (Integrating Reinforcement Learning and Learning From Demonstrations To Learn Nonprehensile Manipulation)

    95-96页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Robotics are disc ussed in a new report. According to newsreporting originating in Shenzhen, Peop le’s Republic of China, by NewsRx journalists, research stated,“Motor skills ar e essential for robots to accomplish complicated and dexterous manipulation task s,which are difficult to be mastered through traditional controller designs. Cu rrently, robots learning fromdemonstrations enable them to learn control polici es automatically from human motor demonstrations.”Financial supporters for this research include National Key Research & Development Program of China,National Natural Science Foundation of China (NSFC ), Guangdong Basic and Applied Basic ResearchFoundation, Shenzhen Fundamental R esearch Program.