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    Recent Studies from Shandong University Add New Data to Robotics (Robot Mapless Navigation In Vuca Environments Via Deep Reinforcement Learning)

    40-41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 reportingoriginating in Jinan, People’s Repub lic of China, by NewsRx journalists, research stated, “Mobile robotsoperating i n unknown social environments demand the ability to navigate among crowds and ot her obstaclesin a safe and socially compliant manner without prior maps. This w ork proposes a deep reinforcementlearning framework for robot mapless navigatio n in such unknown congested and cluttered scenarios.”

    Findings from Chinese Academy of Sciences Advance Knowledge in Robotics [Position control of a soft pneumatic actuator based on the pressure parameter fe edback model (PPFM)]

    41-41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 robotics. According to news originating fromShenyang, People’s Republic of Chin a, by NewsRx correspondents, research stated, “Soft pneumaticactuators have bee n one of the cores of soft robotics research and play a key role in driving the developmentof soft robots.”

    Reproductive Center Reports Findings in Machine Learning (The construction of ma chine learning-based predictive models for highquality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation)

    42-43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 originating from Sichuan, Peo ple’s Republic of China, by NewsRx correspondents, research stated,“To explore the optimal models for predicting the formation of high-quality embryos in Poor OvarianResponse (POR) Patients with Progestin-Primed Ovarian Stimulation (PPOS) using machine learningalgorithms. A retrospective analysis was conducted on th e clinical data of 4,216 POR cycles who underwentin vitro fertilization (IVF) / intracytoplasmic sperm injection (ICSI) at Sichuan Jinxin Xinan Women andChild ren’s Hospital from January 2015 to December 2021.”

    Studies from San Diego State University Update Current Data on Machine Learning (A Hydrologic Signature Approach To Analysing Wildfire Impacts On Overland Flow)

    43-44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 reportingoriginating from San Diego, California, by NewsRx correspondents, research stated, “Post-fire flooding anddebris flows are often triggered by increased overland flow resulting from wildfire impacts o n soil infiltrationcapacity and surface roughness. Increasing wildfire activity and intensification of precipitation with climatechange make improving underst anding of post-fire overland flow a particularly pertinent task.”

    Data on Machine Learning Described by Researchers at Ocean University of China ( Identifying decadal trends in deweathered concentrations of criteria air polluta nts in Canadian urban atmospheres with machine learning approaches)

    44-45页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on artificial intelligen ce have been presented. According to newsoriginating from Qingdao, People’s Rep ublic of China, by NewsRx editors, the research stated, “Thisstudy investigates long-term trends of criteria air pollutants, including NO [ [2] ] , CO, SO [ [2] ] , O [ [3]] and PM [ [2.5] ] , and O [ [* * x* * ] ] (meaning NO [ [2] ] +O [ [3] ] ) measured in 10 Canadiancities during the last 2 to 3 decades. We also investi gated associated driving forces in terms of emissionreductions, perturbations d ue to varying weather conditions and large-scale wildfires, as well as changes in O [ [3] ] sources and sinks.”

    Mansoura University Details Findings in Artificial Intelligence (Silent No More: a Comprehensive Review of Artificial Intelligence, Deep Learning, and Machine L earning In Facilitating Deaf and Mute Communication)

    45-46页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Artificial Intell igence are discussed in a new report. According tonews reporting originating fr om Mansoura, Egypt, by NewsRx correspondents, research stated, “Peoplewho often communicate via sign language are essential to our society and significantly co ntribute. Theystruggle with communication mostly because other people, who ofte n do not understand sign language,cannot interact with them.”

    New Artificial Intelligence Findings from Aalborg University Published (Landscap e and challenges in economic evaluations of artificial intelligence in healthcar e: a systematic review of methodology)

    46-47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 Aalborg University by NewsRx correspondents, research stated, “The potential for artificial intelligence (AI) to transform healthcare cannot be ignored, and the development of AI tec hnologies has increasedsignificantly over the past decade. Furthermore, healthc are systems are under tremendous pressure, andefficient allocation of scarce he althcare resources is vital to ensure value for money.”

    Data on Machine Learning Discussed by Researchers at University of Illinois (Lea rning-assisted Fast Determination of Regularization Parameter In Constrained Ima ge Reconstruction)

    47-48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 reportingfrom Urbana, Illinois, by NewsRx journal ists, research stated, “To leverage machine learning (ML) forfast selection of optimal regularization parameter in constrained image reconstruction. Constraine d imagereconstruction is often formulated as a regularization problem and selec ting a good regularization parametervalue is an essential step.”

    Study Results from State University of New York (SUNY) Buffalo Update Understand ing of Machine Learning (Pydarwin Machine Learning Algorithms Application and Co mparison In Nonlinear Mixed-effect Model Selection and Optimization)

    48-49页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators publish new report on Machine Learn ing. According to news reporting originatingin Buffalo, New York, by NewsRx jou rnalists, research stated, “Forward addition/backward elimination(FABE) has bee n the standard for population pharmacokinetic model selection (PPK) since NONMEM ®was introduced. We investigated five machine learning (ML) algorithms (Geneti c algorithm [GA], Gaussianprocess [GP], random forest [RF] , gradient boosted random tree [GBRT], and particle swarm optimization[PSO]) as alt ernatives to FABE.”

    Nanjing University of Science and Technology Reports Findings in Machine Learnin g (Predicting and refining acid modifications of biochar based on machine learni ng and bibliometric analysis: Specific surface area, average pore size, and tota l …)

    49-50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 out of Nanjing, People’s Repu blic of China, by NewsRx editors, research stated, “Acid-modifiedbiochar is a m odified biochar material with convenient preparation, high specific surface area , and richpore structure. It has great potential for application in the heavy m etal remediation, soil amendments andcarrying catalysts.”