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    Researchers’ Work from NORSAR Focuses on Machine Learning (Estimating Stratosphe ric Polar Vortex Strength Using Ambient Ocean-generated Infrasound and Stochasti cs-based Machine Learning)

    40-41页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Kjeller, Norwa y, by NewsRx journalists, research stated, “There are sparse opportunities for d irect measurement of upper stratospheric winds, yet improving their representati on in subseasonal-to-seasonal prediction models can have significant benefits. T here is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics.” Financial supporters for this research include NORSAR, Research Council of Norway.

    Studies from Indiana University Southeast Update Current Data on Artificial Inte lligence (A Moderated Model of Artificial Intelligence Adoption In Firms and Its Effects On Their Performance)

    41-41页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Artificial Intelligence. According to news reporting from New Albany, Indiana, b y NewsRx journalists, research stated, “Leveraging two prominent theories of tec hnology adoption in firms, this study examines the organizational determinants o f the adoption intensity of artificial intelligence (AI) and its effects on firm s’ performance, under the moderating effects of technological turbulence. To con duct this study, a unique dataset was compiled via a survey of USbased managers involved with technology and AI adoption in high-tech goods and services, leadi ng to 226 usable responses.”

    Reports Outline Machine Learning Findings from Chinese Academy of Sciences (Impa ct of Structural Characteristics On Thermal Conductivity of Foam Structures Reve aled With Machine Learning)

    42-43页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting from Shenzhen, People’s Republic o f China, by NewsRx journalists, research stated, “The foam-like structures have been shown to facilitate thermal transport efficiency by forming 3D-network heat conduction pathways, which shows broad applications in thermal management. Howe ver, the design of foam structures with desired thermal transport property is tr icky because of the complexity of the structures and their relationship with the property.”

    University of Campania Luigi Vanvitelli Reports Findings in Artificial Intellige nce (Toward Nano- and Microplastic Sensors: Identification of Nano- and Micropla stic Particles via Artificial Intelligence Combined with a Plasmonic Probe ...)

    43-43页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Aversa, Italy, by NewsRx journalists, research stated, “Nano- and microplastic particles are a gl obal and emerging environmental issue that might pose potential threats to human health. The present work exploits artificial intelligence (AI) to identify nano - and microplastics in water by monitoring the interaction of the sample with a sensitive surface.”

    Reports Outline Robotics Study Findings from University of Almeria (Robotics In Greenhouses. Scoping Review)

    44-44页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Robotics. According to news originating from Almeria, Spain, by NewsRx correspon dents, research stated, “One of the main initiatives to increase the profit, pro duction, and quality of greenhouse horticulture, as well as its sustainability, is the use of robots. This paper focusses on the state-of-the-art of the use of robots in greenhouses since the 1980 s on the basis of the PRISMA methodology.”

    Cheng Shiu University Researcher Adds New Study Findings to Research in Robotics (Examining the performance of Laguerre-based and nonlinear predictive control m odels for wheeled mobile robots when facing obstacles)

    45-45页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ro botics. According to news reporting originating from Kaohsiung City, Taiwan, by NewsRx correspondents, research stated, “This focuses on the problem of controll ing the formation of a team of rotating robots that are not homonomic and are no t able to interact in a barrier environment. The virtual structure formation con trol strategy is obtained here to calculate each path of the robot separately wh ile the reference path of the virtual center of the formation is generated by ar tificial potential fields.”

    Research Data from Renmin University of China Update Understanding of Artificial Intelligence (Exploring the Potentials of Artificial Intelligence Towards Carbo n Neutrality: Technological Convergence Forecasting Through Link Prediction and ...)

    46-47页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Artificial In telligence have been published. According to news reporting originating in Beiji ng, People’s Republic of China, by NewsRx journalists, research stated, “To expl ore future opportunities for artificial intelligence (AI) in achieving carbon ne utrality goals, this study introduces a forecasting framework that combines link prediction and community detection. The proposed framework begins by utilizing patent information and the International Patent Classification to construct a co occurrence network.”

    Texas State University Researcher Adds New Study Findings to Research in Machine Learning (Comparing Machine Learning and Time Series Approaches in Predictive M odeling of Urban Fire Incidents: A Case Study of Austin, Texas)

    47-47页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news reporting from San Marcos, Texas, by NewsRx journalists, research stated, “This study examines urban fire incidents in Austi n, Texas using machine learning (Random Forest) and time series (Autoregressive integrated moving average, ARIMA) methods for predictive modeling.” Financial supporters for this research include Microsoft Ai For Earth Grant.

    New Agricultural Robots Findings from Jiangsu University Described (Apple Recogn ition and Picking Sequence Planning for Harvesting Robot In a Complex Environment)

    48-48页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Agriculture - Agr icultural Robots are discussed in a new report. According to news reporting orig inating from Jiangsu, People’s Republic of China, by NewsRx correspondents, rese arch stated, “In order to improve the efficiency of robots picking apples in cha llenging orchard environments, a method for precisely detecting apples and plann ing the picking sequence is proposed. Firstly, the EfficientFormer network serve s as the foundation for YOLOV5, which uses the EF-YOLOV5s network to locate appl es in difficult situations.”

    Research on Machine Learning Published by Researchers at School of Electrical En gineering (Open-Circuit Fault Diagnosis for a Modular Multilevel Converter Based on Hybrid Machine Learning)

    49-49页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting from the School of Electric al Engineering by NewsRx journalists, research stated, “With the wide applicatio n of a modular multilevel converter in various power conversion fields, submodul e open-circuit fault diagnostics have attracted increasing attention, as some of the existing diagnosis methods have a single function and limited localization speed.”