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

    AI alters middle managers work

    1-2页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - The introduction of artificial intelligence is a significant part of the digital transformationbringing challenges and changes to the job descriptions among management. A study conducted atthe University of Eastern Finland shows that integrating artificial intelligence systems into service teamsincreases demands imposed on middle management in the financial services field. In that sector, the adventof artificial intelligence has been fast and AI applications can implement a large proportion of routine workthat was previously done by people. Many professionals in the service sector work in teams which includeboth humans and artificial intelligence systems, which sets new expectations on interactions, humanrelations, and leadership.

    Researchers at Federal University of Technology Have Published New Study Findings on Machine Learning (An adaptive neuro-fuzzy inference system white-box model for real-time multiphase flowing bottom-hole pressure prediction in wellbores)

    2-3页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Researchers detail new data in artificial intelligence. According to news reporting originatingfrom Owerri, Nigeria, by NewsRx correspondents, research stated, “The majority of published empiricalcorrelations and mechanistic models are unable to provide accurate flowing bottom-hole pressure (FBHP)predictions when real-time field well data are used. This is because the empirical correlations and theempirical closure correlations for the mechanistic models were developed with experimental datasets.”

    University of Toronto Researcher Focuses on Machine Learning (Identification of Myofascial Trigger Point Using the Combination of Texture Analysis in B-Mode Ultrasound with Machine Learning Classifiers)

    3-4页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New study results on artificial intelligence have been published. According to newsreporting originating from Toronto, Canada, by NewsRx correspondents, research stated, “Myofascial painsyndrome is a chronic pain disorder characterized by myofascial trigger points (MTrPs).”

    Investigators at University of Washington Describe Findings in Machine Learning (An Accelerated Process Optimization Method To Minimize Deformations In Composites Using Theory-guided Probabilistic Machine Learning)

    4-5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 originating fromSeattle, Washington, by NewsRx correspondents, research stated, “While aerospace manufacturing andassembly technologies have significantly evolved, challenges persist in mitigating process-induced deformations(PIDs) in composite parts. Physics-based-simulation optimization strategies have been developed toaddress these challenges.”

    Researchers from Jilin University Report Findings in Machine Learning (Applying Machine-learning Screening of Single Transition Metal Atoms Anchored On N-doped G-graphyne for Carbon Monoxide Electroreduction Toward C1 Products)

    5-5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. Accordingto news reporting originating from Changchun, People’s Republic of China, by NewsRx correspondents,research stated, “Carbon monoxide electroreduction (COER) has been a key part of tandem electrolysis ofcarbon dioxide (CO2), in which searching for high catalytic performance COER electrocatalysts remainsa great challenge. Herein, by means of density functional theory (DFT) computations, we explored thepotential of a series of transition metal atoms anchored on N-doped gamma-graphyne (TM@N-GY, TMfrom Ti to Au) as the COER electrocatalysts.”

    New Findings Reported from Tongji University Describe Advances in Machine Learning (Effects of Buffer Size On Associations Between the Built Environment and Metro Ridership: a Machine Learningbased Sensitive Analysis)

    6-6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 Machine Learning. According to news reportingout of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “Uncertainty in therelevant buffer size of metro station catchment areas may drive inconsistencies in the findings on the builtenvironment and metro ridership. Although previous studies estimate the effect of this uncertainty, theresults are far from definitive.”

    Study Results from Tianjin University in the Area of Machine Learning Reported (Machine Learning Prediction of Flavonoid Cocrystal Formation Combined With Experimental Validation)

    7-7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 Learning have been published. According to newsreporting originating from Tianjin, People’s Republic of China, by NewsRx correspondents, research stated,“This study established a flavonoid cocrystal database, and four machine learning models [support vectormachine (SVM), random forest (RF), logistic regression (LR), and artificial neural network (ANN)]were established to screen flavonoid cocrystal coformers based on three screening methods of the moleculardescriptors [original, principal component analysis (PCA)-selected, and quantitative structure-propertyrelationship (QSPR)-selected descriptors].”

    Shanghai Jiao Tong University Reports Findings in COVID-19 (Identification of key gene expression associated with quality of life after recovery from COVID-19)

    8-8页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Coronavirus - COVID-19 is the subject of a report. According to news reportingfrom Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “Post-acute sequelae ofCOVID-19 (PASC) is a persistent complication of severe acute respiratory syndrome coronavirus 2 infectionthat includes symptoms, such as fatigue, cognitive impairment, and respiratory distress. These symptomsseverely affect the quality of life of patients after their recovery from COVID-19.”

    New Findings from Indian Institute of Technology IIT Roorkee in Machine Learning Provides New Insights (Ml-avat: a Novel 2-stage Machine-learning Approach for Automatic Clustering Tendency Assessment)

    9-9页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news originatingfrom Roorkee, India, by NewsRx correspondents, research stated, “Clustering tendency assessment, whichaims to deduce if a dataset contains any cluster structure, and, if it does, how many clusters it has, is acritical problem in exploratory data analysis. The VAT family of algorithms provides a ‘visual’ means toassess the clustering tendency for various datasets.”

    Researchers from University of California Los Angeles (UCLA) Report on Findings in Machine Learning (Integrating Machine Learning Detection and Encrypted Control for Enhanced Cybersecurity of Nonlinear Processes)

    10-11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 Los Angeles, California, by NewsRx editors, research stated, “This study presents anencrypted two-tier control architecture integrated with a machine learning (ML) based cyberattack detectorto enhance the operational safety, cyber-security, and performance of nonlinear processes. The upper tierof this architecture employs an encrypted nonlinear Lyapunov-based model predictive controller (LMPC)to enhance closed-loop performance, while the lower tier utilizes an encrypted set of linear controllers tostabilize the process.”