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    Researchers from Tsinghua University Report Details of New Studies and Findings in the Area of Machine Learning (Interpretable Machine Learning To Discover Perovskites With High Spontaneous Polarization)

    84-84页
    查看更多>>摘要:Investigators discuss new findings in Machine Learning. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Machine learning can accelerate the design of new materials by screening large quantities of materials. We investigated the spontaneous polarization intensity of inorganic perovskite ferroelectrics using a machine learning approach.”

    Nara Institute of Science and Technology Researchers Release New Data on Robotics (Do as I Demand, Not as I Say: A Dataset for Developing a Reflective Life-Support Robot)

    85-85页
    查看更多>>摘要:Data detailed on robotics have been presented. According to news reporting from Ikoma, Japan, by NewsRx journalists, research stated, “Interactive robots that cooperate with humans must take appropriate actions in response to their requests.”

    University of Groningen Reports Findings in Machine Learning (Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT)

    85-86页
    查看更多>>摘要:New research on Machine Learning is the subject of a report. According to news reporting from Groningen, Netherlands, by NewsRx journalists, research stated, “Detecting ablation site recurrence (ASR) after thermal ablation remains a challenge for radiologists due to the similarity between tumor recurrence and post-ablative changes. Radiomic analysis and machine learning methods may show additional value in addressing this challenge.”

    University of Modena and Reggio Emilia Researchers Release New Study Findings on Machine Learning (Bearing Fault Detection and Recognition From Supply Currents With Decision Trees)

    86-87页
    查看更多>>摘要:Investigators publish new report on artificial intelligence. According to news originating from Reggio Emilia, Italy, by NewsRx editors, the research stated, “This paper considers the tasks of detecting and recognizing bearing faults in electric motors from the signals collected from supply currents, using machine learning techniques.”

    New Machine Learning Research Has Been Reported by Researchers at National University of Science and Technology (NUST) (Multimodal LSTM network for anomaly prediction in piston engine aircraft)

    87-88页
    查看更多>>摘要:New research on artificial intelligence is the subject of a new report. According to news originating from National University of Science and Technology (NUST) by NewsRx correspondents, research stated, “An aircraft is a highly intricate system that features numerous subsystems, assemblies, and individual components for which regular maintenance is inevitable. The operational efficiency of an aircraft can be maximised, and its maintenance needs can be reduced using an effective yet automatic AI-based health monitoring systems which are more efficient as compared to designing and constructing expensive and harder to operate engine testbeds.”

    University of Limpopo Researchers Focus on Machine Learning (Machine learning models for predicting density of sodium-ion battery materials)

    88-89页
    查看更多>>摘要:Fresh data on artificial intelligence are presented in a new report. According to news reporting out of the University of Limpopo by NewsRx editors, research stated, “With the unprecedented amounts of material data generated from high-throughput density functional theory, machine learning provides the ability to accelerate the discovery and design of new materials.”

    Report Summarizes Robotics Study Findings from Kongu Engineering College (Semi-Automatic Child Rescuing BOT in Deep Borewell)

    89-89页
    查看更多>>摘要:Data detailed on robotics have been presented. According to news originating from Kongu Engineering College by NewsRx correspondents, research stated, “Rescue operations for people trapped in deep borewells provide a serious problem needing both advanced robotic technology and human expertise.”

    Shanghai Jiao Tong University Reports Findings in Lung Cancer (Value of multi-center 18 F-FDG PET/CT radiomics in predicting EGFR mutation status in lung adenocarcinoma)

    90-91页
    查看更多>>摘要:New research on Oncology - Lung Cancer is the subject of a report. According to news reporting from Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “Accurate, noninvasive, and reliable assessment of epidermal growth factor receptor (EGFR) mutation status and EGFR molecular subtypes is essential for treatment plan selection and individualized therapy in lung adenocarcinoma (LUAD). Radiomics models based on F-FDG PET/CT have great potential in identifying EGFR mutation status and EGFR subtypes in patients with LUAD.”

    Researchers from Xi’an Technological University Report Details of New Studies and Findings in the Area of Support Vector Machines (Fault Diagnosis of High-speed Rolling Bearing In the Whole Life Cycle Based On Improved Grey Wolf Optimizer-least ...)

    91-92页
    查看更多>>摘要:A new study on Support Vector Machines is now available. According to news originating from Xi’an, People’s Republic of China, by NewsRx correspondents, research stated, “Under the high-speed condition, the fault diagnosis of rolling bearing is difficult due to parameter limitation and local optimization. To solve these problems, a fault diagnosis method of the whole life cycle based on wavelet thresholding denoising, genetic algorithm-variational mode decomposition (GA-VMD) and improved grey wolf optimizer-least squares support vector machines (IGWO-LSSVM) is proposed.”

    Reports from Tianjin University Provide New Insights into Robotics (A Dynamic Parameter Identification Method for the 5-dof Hybrid Robot Based On Sensitivity Analysis)

    92-93页
    查看更多>>摘要:Financial support for this research came from National Natural Science Foundation of China (NSFC). The news correspondents obtained a quote from the research from Tianjin University, “Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.