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

    New Machine Learning Findings from University of Victoria Outlined (Applying Mac hine Learning To Elucidate Ultrafast Demagnetization Dynamics In Ni and Ni80fe20 )

    57-58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 originating in Victoria, Ca nada, by NewsRx journalists, research stated, “Understanding thecorrelation bet ween fast and ultrafast demagnetization (UFD) processes is crucial for elucidati ng themicroscopic mechanisms underlying UFD, which is pivotal for various appli cations in spintronics. Initialtheoretical models attempt to establish this cor relation but face challenges due to the complex interplayof physical phenomena. ”

    Studies from Hefei University of Technology Update Current Data on Robotics (Dee p Reinforcement Learning Driven Cost Minimization for Batch Order Scheduling In Robotic Mobile Fulfillment Systems)

    58-59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 reporting originating in Anhui,People’s Republic of China, by Ne wsRx journalists, research stated, “Robotic Mobile Fulfillment Systems(RMFS) ar e extensively employed in modern warehouses. In the era of booming e-commerce, t hisparts-to-picker model significantly reduces warehouse costs and enhances ope rational efficiency.”Financial supporters for this research include National Natural Science Foundati on of China (NSFC),National Key Research & Development Program of China.

    Lanzhou University Reports Findings in Diabetic Nephropathy (Development and ext ernal validation of a machine learning model to predict diabetic nephropathy in T1DM patients in the real-world)

    59-60页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Kidney Diseases and Co nditions - Diabetic Nephropathy is thesubject of a report. According to news re porting originating from Gansu, People’s Republic of China,by NewsRx correspond ents, research stated, “Studies on machine learning (ML) for the prediction of diabetic nephropathy (DN) in type 1 diabetes mellitus (T1DM) patients are rare. T his study focused onthe development and external validation of an explainable M L model to predict the risk of DN amongindividuals with T1DM.”

    Study Results from National Center for Scientific Research (CNRS) in the Area of Machine Learning Reported (Unsupervised Machine Learning Classification for Acc elerating Fe2 Multiscale Fracture Simulations)

    60-61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 Marne la Vallee, France , by NewsRx correspondents, research stated, “An approachis proposed to acceler ate multiscale simulations of heterogeneous quasi-brittle materials exhibiting a nanisotropic damage response. The present technique uses unsupervised machine l earning classificationbased on k-means clustering to select integration points in the macro mesh within an FE2 2 strategyto track redundant micro nonlinear pr oblems and to avoid unnecessary Representative Volume Element(RVE) calculations .”

    Findings from Sichuan University Yields New Data on Machine Learning (An Enhance d Hybrid Approach for Spatial Distribution of Seismic Liquefaction Characteristi cs By Integrating Physics-based Simulation and Machine Learning)

    61-62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 originatingfrom Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “This study aimsto propose a n enhanced hybrid approach that combines physics-based simulation and machine le arningto investigate the spatial distribution of seismic liquefaction character istics. This innovative approachcomprises two main components: Firstly, the phy sics-based frequency-wavenumber method is employedto construct the spatial-temp oral field of ground motion in the study area, which provides ground motionquan tities for assessing the liquefaction characteristic (e.g., liquefaction potenti al index) of the site.”

    Studies Conducted at University of Denver on Machine Learning Recently Reported (Pooling and Winsorizing Machine Learning Forecasts To Predict Stock Returns Wit h High-dimensional Data)

    62-63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 reportingout of Denver, Colorado, by NewsRx editors, research stated, “We evaluate US market return predictabilityusing a novel data set of several hundred ag- gregated firm-level characteristics. We ap ply LASSO, ElasticNet, Random Forest, Neural Net, Extreme Gradient Boosting, an d Light Gradient Boosting Machinemethods and find these models experience large prediction errors that lead to forecast failures.”

    University of Science and Technology of China Reports Findings in COVID-19 (Mach ine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding)

    63-64页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Coronavirus - COVID-19 is the subject of a report. According tonews reporting from Anhui, People’s Re public of China, by NewsRx journalists, research stated, “Theglobal outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in whichprolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2, previously 2019-nCoV) infection is a challenge in the prevention and treatmen t of COVID-19. However, there is stillincomplete research on the risk factors t hat affect delayed shedding of SARS-CoV-2.”

    Lanzhou Jiaotong University Reports Findings in Machine Learning [Explainable machine learning models for predicting the acute toxicity of pestici des to sheepshead minnow (Cyprinodon variegatus)]

    64-65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 Gansu, People’s Republ ic of China, by NewsRx editors, research stated, “A quantitativestructure-activ ity relationship (QSAR) study was conducted on 313 pesticides to predict their a cute toxicityto Sheepshead minnow (Cyprinodon variegatus) by using DRAGON descr iptors. Essentials accounting fora reliable model were all considered carefully , giving full consideration to the OECD (Organization forEconomic Co-operation and Development) principles for QSAR acceptability in regulation during the model construction and assessment process.”

    Reports from Banaras Hindu University Describe Recent Advances in Machine Learni ng (Machine Learning Approach for Detection of Land Subsidence Induced By Underg round Coal Fire Using Multisensor Satellite Data)

    65-66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 reportingfrom Varanasi, India, by NewsRx jour nalists, research stated, “High-rank coal reserves in Jharia Coalfield(JCF, Ind ia), are invariably associated with underground coal fires and land subsidence. This study exploresmulti-sensor time series satellite data (Landsat 8 OLI and S entinel-1) through machine learning (ML) todetermine the regional ground deform ation accompanying coal fires and their contextual relationship.”

    University of Health Sciences Reports Findings in Nephropathy (Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropa thy in NSTEMI patients)

    66-67页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Kidney Diseases and Conditions - Nephropathy is the subject of a report. Accordingto news reporting out of Istan bul, Turkey, by NewsRx editors, research stated, “Inflammatory prognosticindex (IPI), has been shown to be related with poor outcomes in cancer patients. We ai med to investigatethe predictive role of IPI for contrast-induced nephropathy ( CIN) development in non-ST segment elevationmyocardial infarction patients usin g a nomogram and performing machine learning (ML) algorithms.”