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    Researchers from Tianjin University Detail Findings in Machine Learning (Combina tion of Integrated Machine Learning Model Frameworks and Infrared Spectroscopy T owards Fast and Interpretable Characterization of Model Pyrolysis Oil)

    184-185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 reportingfrom Tianjin, People’s Republic of China, by NewsRx journalists, research stated, “Model pyrolysis oil(bio-oil) i s a promising bio-fuel with complex and unstable contents, making its fast chara cterization anessential demand in industrial production. This study proposed an integrated machine learning frameworkto predict elemental composition, low hea ting value, and unsaturated concentration from infrared spectra,achieving fast and interpretable characterization of bio-oil.”

    New Artificial Intelligence Study Findings Recently Were Reported by Researchers at Xiamen University (Artificial Intelligence Driven Tunneling-induced Surface Settlement Prediction)

    185-185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 originatingfrom Xiamen, People’s Republic o f China, by NewsRx correspondents, research stated, “There has beenan increasin g demand for shield tunnel construction due to the extensive utilization and lim ited land inmetropolitan cities. However, the behaviors of soils and rocks exhi bit a high level of uncertainty in materialmodeling.”

    Researchers at Nanjing University of Information Science and Technology (NUIST) Target Robotics (Optimization of Percutaneous Intervention Robotic System for Sk in Insertion Force)

    186-186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 Robotics is now availab le. According to news originating from Nanjing,People’s Republic of China, by N ewsRx correspondents, research stated, “PurposePercutaneous punctureis a common interventional procedure, and its effectiveness is influenced by the insertion force of the needle.To optimize outcomes, we focus on reducing the peak force o f the needle in the skin, aiming to apply thismethod to other tissue layers.Met hodsWe developed a clinical puncture system, setting and measuringvarious varia bles.”

    Department of Urology Reports Findings in Nephrectomy (Robotassisted partial ne phrectomy vs. percutaneous cryoablation for T1a renal tumors: a single-center re trospective analysis of outcomes and costs)

    187-187页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Surgery - Nephrectomy is the subject of a report. According tonews reporting originating from Avellin o, Italy, by NewsRx correspondents, research stated, “The aimof this study is t o compare perioperative, functional, and oncological outcomes between robot-assi stedpartial nephrectomy (RAPN) and cryoablation (CRYO), based on a 3-year exper ience at our Institution.Additionally, a secondary aim is to conduct a comparat ive cost analysis between the two procedures.”

    Oak Ridge National Laboratory Researchers Release New Study Findings on Machine Learning (Exploring electron-beam induced modifications of materials with machin e-learning assisted high temporal resolution electron microscopy)

    188-188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 the Oak Ridge National Laboratory by NewsRx editors, research stated, “Directed atomicfabric ation using an aberration-corrected scanning transmission electron microscope (S TEM) opens newpathways for atomic engineering of functional materials.”

    Zhejiang University School of Medicine Reports Findings in Machine Learning (Dev elopment and validation of a machine learning model to predict the risk of readm ission within one year in HFpEF patients: Short title: Prediction of HFpEF …)

    189-189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 Hangzhou, People’s Repub lic of China, by NewsRx journalists, research stated, “Heartfailure with preser ved ejection fraction (HFpEF) is associated with elevated rates of readmission a ndmortality. Accurate prediction of readmission risk is essential for optimizin g healthcare resources andenhancing patient outcomes.”

    Researcher at Southwest University of Science and Technology Details Research in Robotics (An Anti-Interference Control Algorithm for Continuum Robot Arm)

    190-190页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators discuss new findings in robotics. A ccording to news reporting originating fromMianyang, People’s Republic of China , by NewsRx correspondents, research stated, “The large numberof joints in a co ntinuum manipulator complicates its dynamic modeling, making model simplificatio ninevitable for practical motion control.”

    Studies from University of Twente Further Understanding of Machine Learning (Gre en Ai In the Finance Industry: Exploring the Impact of Feature Engineering On th e Accuracy and Computational Time of Machine Learning Models)

    190-191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 newsoriginating from Enschede, Netherlands, by NewsRx correspondents, research stated, “As research andpractice in Artific ial Intelligence (AI) applications rapidly expand, the support for AI deployment is alsoincreasing. While the abundance of data allows for sophisticated featur e engineering techniques that can enhance accuracy, it is crucial to highlight b oth the computational costs and the efficiency with whichthese models operate.”

    New Machine Learning Findings Reported from University of Louisville (Response T ime of Fast Flowing Hydrologic Pathways Controls Sediment Hysteresis In a Low-gr adient Watershed, As Evidenced From Tracer Results and Machine Learning Models)

    191-192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 tonews reporting from Louisville, Kentucky, by NewsRx journalists, research stated, “Hydrologic controlson the timing of se diment transport and sediment hysteresis patterns remain an open area of investigation in hydrology, especially for low-gradient watersheds with substantial ins tream sediment deposition.

    University of Oklahoma Reports Findings in Machine Learning (MetaPhenotype: A Tr ansferable Meta-Learning Model for Single- Cell Mass Spectrometry-Based Cell Phen otype Prediction Using Limited Number of Cells)

    193-193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 newsoriginating from Norman, Oklahoma, by N ewsRx correspondents, research stated, “Single-cell mass spectrometry(SCMS) is an emerging tool for studying cell heterogeneity according to variation of molec ularspecies in single cells. Although it has become increasingly common to empl oy machine learning modelsin SCMS data analysis, such as the classification of cell phenotypes, the existing machine learning modelsoften suffer from low adap tability and transferability.”