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

    Findings from VTT Technical Research Centre of Finland Ltd. Broaden Understandin g of Robotics (Dynamic and probabilistic safety zones for autonomous mobile robo ts operating near humans)

    28-29页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on robotics have been pr esented. According to news reporting originatingfrom the VTT Technical Research Centre of Finland Ltd. by NewsRx correspondents, research stated, “Theineffici ency of maintaining static and long-lasting safety zones in environments where a ctual risks arelimited is likely to increase in the coming decades, as autonomo us systems become more common andhuman workers fewer in numbers.”

    University of Sao Paulo Details Findings in Machine Learning (Streamflow Regiona lization In Brazil: Traditional Methods and State of the Art)

    29-30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 newsreporting out of Piracicaba, Brazil, b y NewsRx editors, research stated, “Water resources managementaims to solve pro blems arising from intensive use of water. The proper management of this resourc e isbased on understanding water availability, often using information from hyd rometric stations; flow data isthe most important information.”

    Findings from Ningbo University Provides New Data on Machine Learning (Machine-l earning-based Numerical Solution for Low and Lou’s Nonlinear Force-free Field Eq uilibria)

    30-31页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news originatingfrom Zhejiang, People’s Republic of Chi na, by NewsRx correspondents, research stated, “Low and Lou(Astrophys. J.352, 3 43, 1990) presented a family of nonlinear force-free magnetic fields that have established themselves as the gold standard for extrapolating force-free magnetic fields in solar physics.”

    New Findings on Robotics from Nanjing University of Science and Technology Summa rized (A Novel Hybrid Observer-based Modelfree Adaptive High-order Terminal Sli ding Mode Control for Robot Manipulators With Prescribed Performance)

    31-32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 reportingfrom Nanjing, People’s Republic of Ch ina, by NewsRx journalists, research stated, “Although widely usedin industrial applications, strong nonlinearity and coupling, high computational complexity p revent highprecision tracking control of manipulator. In this paper, to overcom e the rely on system model and achieveprescribed convergence, a novel hybrid ob server-based model-free adaptive high-order fast terminal slidingmodel control scheme (HO-MHTSMC) with prescribed performance is proposed for trajectory tracki ngcontrol of robot manipulators in the existence of friction and external distu rbance.”

    Findings in the Area of Artificial Intelligence Reported from RWTH Aachen Univer sity (Artificial Intelligence In Acute Care: a Systematic Review, Conceptual Syn thesis, and Research Agenda)

    32-33页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Artific ial Intelligence. According to news reportingout of Aachen, Germany, by NewsRx editors, research stated, “Artificial intelligence (AI) is emerging as apromisi ng healthcare technology. Especially in critical, data-driven, and complex envir onments such asacute care, the use of AI can significantly improve treatment pr ocesses and support clinical staff.”

    Studies from Beijing University of Chinese Medicine Add New Findings in the Area of Machine Learning (Machine Learning-based Analysis and Prediction of Meteorol ogical Factors and Urban Heatstroke Diseases)

    33-34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 Machine Learning is now available. According to news reporting originatingfrom Beijing, People’s Repub lic of China, by NewsRx correspondents, research stated, “Heatstrokeis a seriou s clinical condition caused by exposure to high temperature and high humidity en vironment,which leads to a rapid increase of the core temperature of the body t o more than 40 degrees C, accompaniedby skin burning, consciousness disorders a nd other organ system damage. This study aims toanalyze the effect of meteorolo gical factors on the incidence of heatstroke using machine learning, andto cons truct a heatstroke forecasting model to provide reference for heatstroke prevent ion.Methods Thedata of heatstroke incidence and meteorological factors in a cit y in South China from May to September2014-2019 were analyzed in this study.”

    Washington State University Reports Findings in Machine Learning (Machine Learni ng Application for Predicting Key Properties of Activated Carbon Produced From L ignocellulosic Biomass Waste With Chemical Activation)

    34-35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 Richland, Washington, by NewsRx journalists, research stated, “The successful applicationof gradient bo osting regression (GBR) in machine learning to forecast surface area, pore volum e, and yieldin biomass-derived activated carbon (AC) production underscores its potential for enhancing manufacturingprocesses.”

    Reports from Huaqiao University Provide New Insights into Computational Intellig ence (Adversarial Attention Networks for Early Action Recognition)

    35-36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 - Computational Intelligence.According to news reporting origina ting from Xiamen, People’s Republic of China, by NewsRx correspondents,research stated, “Early action recognition endeavors to deduce the ongoing action by obs ervingpartial video, presenting a formidable challenge due to limited informati on available in the initial stages.To tackle this challenge, we introduce an in novative adversarial attention network based on generativeadversarial networks. ”

    Fudan University Reports Findings in Solid Cancer (Fast prediction of personaliz ed abdominal organ doses from CT examinations by radiomics feature-based machine learning models)

    36-36页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Oncology - Solid Cance r is the subject of a report. According tonews originating from Shanghai, Peopl e’s Republic of China, by NewsRx correspondents, research stated,“The X-rays em itted during CT scans can increase solid cancer risks by damaging DNA, with the risk tiedto patient-specific organ doses. This study aims to establish a new me thod to predict patient specificabdominal organ doses from CT examinations usin g minimized computational resources at a fast speed.”

    Research Conducted at Phenikaa University Has Updated Our Knowledge about Machin e Learning (A Comparative Study of Machine Learning Models for Identifying Noxio us Gases Through Thermal Fingerprint Measurements and Mos Sensors)

    37-37页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. According tonews reporting out of Hanoi, Vietnam , by NewsRx editors, research stated, “Recently, there has been anotable surge of interest in developing swift and precise gas detection and categorization too ls throughartificial intelligence. This work specifically focuses on designing a simple sensor array configuration andempirically compares various machine-lea rning models for identifying multiple gases.”