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

    Study Data from Nanjing Normal University Provide New Insights into Machine Lear ning (Tree-structured Parzen Estimator Optimized-automated Machine Learning Assi sted By Meta-analysis for Predicting Biochar-driven N2o Mitigation Effect In ... )

    84-85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 Machine Learning are discussed in a new report. According to news reporting out of Nanjing, Peopl e’s Republic of China, by NewsRx editors, research stated, “Biochar is a carbon- neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions.”Funders for this research include National Natural Science Foundation of China ( NSFC), National Key Research and Development Program, Ministry of Science and Te chnology, China, Province Key Research and Development Pro- gram of Jiangsu, Chi na, Postgraduate Research & Practice Innovation Program of Jiangsu Province of China.
      原文链接:
    • NETL
    • NSTL

    New Machine Learning Study Findings Reported from Lanzhou University (GIS and Ma chine Learning Models Target Dynamic Settlement Patterns and Their Driving Mecha nisms from the Neolithic to Bronze Age in the Northeastern Tibetan Plateau)

    86-87页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news originating from Lanzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Traditional GIS- based statistical models are intended to extrapolate patterns of settlements and their interactions with the environment. They contribute significantly to our k nowledge of past human-land relationships.” Funders for this research include Nsfc-insf Joint Research Project; Second Tibet an Plateau Scientific Expedition And Research Program; Academician And Expert Wo rkstation of Yunnan Province; European Research Council.
      原文链接:
    • NETL
    • NSTL

    University of Debrecen Researchers Provide New Data on Robotics (Accepting a rob ot request contradicting a human instruction in the function of robot attitudes and level of interdependency)

    86-86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 out of Debrecen, Hungary, by NewsRx editors, research stated, “Collaboration with robots requires robot acceptance, but it c an have adverse consequences when people accept a robot’s request against their best intuition or another request from a superior human.” Funders for this research include University of Debrecen.
      原文链接:
    • NETL
    • NSTL

    New Findings from Jilin University Describe Advances in Machine Learning (High-p erformance Imbalanced Learning Ensembles of Decision Trees for Detecting Mineral ization Anomalies From Geochemical Exploration Data)

    88-89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 Machine Learn ing have been published. According to news reporting from Jilin, People’s Republ ic of China, by NewsRx journalists, research stated, “How to effectively detect geochemical anomalies associated with mineralization is a challenging task due t o the extreme classimbalance of geochemical exploration data. To address this c hallenge, various machine learning techniques have been employed to detect geoch emical anomalies associated with mineralization.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
      原文链接:
    • NETL
    • NSTL

    China Academy of Building Research Researchers Describe Advances in Machine Lear ning (A Forest Fire Prediction Model Based on Cellular Automata and Machine Lear ning)

    89-90页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Beijing, Peopl e’s Republic of China, by NewsRx editors, research stated, “Forest fires constit ute a widespread and impactful natural disaster, annually ravaging millions of h ectares of forests and posing a severe threat to human life and property. Accura te quantitative prediction of forest fire spread is essential for devising swift risk management strategies and implementing effective firefighting approaches.” Funders for this research include Fundamental Research Funds For The Central Uni versities; King Saud University.
      原文链接:
    • NETL
    • NSTL

    New Findings from Shanghai Jiao Tong University in the Area of Robotics Reported (Forward Kinematics of Object Transporting By a Multi-robot System With a Defor mable Sheet)

    90-91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 Robotics are disc ussed in a new report. According to news reporting originating from Shanghai, Pe ople’s Republic of China, by NewsRx correspondents, research stated, “We present a forward kinematics method for object handling and transporting by a multi-rob ot team with a deformable sheet as a carrier. Due to the deformability of the sh eet and the high dimension of the whole system, it is challenging to clearly des cribe all the possible positions of the object on the sheet for a given formatio n of the multi-robot system.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
      原文链接:
    • NETL
    • NSTL

    National Chung Hsing University Researcher Yields New Study Findings on Machine Learning (Integrating machine learning and feature analysis for predicting and m anaging thermal deformation in machine tools)

    90-90页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting from Taichung, Taiwan , by NewsRx journalists, research stated, “This study develops a method to predi ct and compensate for thermal deformation in machine tools, focusing on selectin g temperaturesensitive points, establishing a predictive model, and detecting t emperature anomalies.” The news reporters obtained a quote from the research from National Chung Hsing University: “Optimal sensing points were identified using feature ranking algori thms and Partial Dependence Plots, improving Z-axis deformation identification. The research also evaluated various machine learning models for Z-axis deformati on prediction, notably optimizing Gaussian Process Regression for superior accur acy. Additionally, anomaly detection in temperature sensors was addressed using One-Dimensional Convolutional Neural Networks and Long Short-Term Memory Network s, enhancing system reliability and robustness.”
      原文链接:
    • NETL
    • NSTL

    Data on Artificial Intelligence Reported by Teodora Karteva and Colleagues (Arti ficial intelligence and smile design: An e-Delphi consensus statement of ethical challenges)

    91-92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 Berlin, Germany, by NewsRx journalists, research stated, “Smile design software increasingly reli es on artificial intelligence (AI). However, using AI for smile design raises nu merous technical and ethical concerns.” The news correspondents obtained a quote from the research, “This study aimed to evaluate these ethical issues. An international consortium of experts specializ ed in AI, dentistry, and smile design was engaged to emulate and assess the ethi cal challenges raised by the use of AI for smile design. An e- Delphi protocol wa s used to seek the agreement of the ITU-WHO group on well-established ethical pr inciples regarding the use of AI (wellness, respect for autonomy, privacy protec tion, solidarity, governance, equity, diversity, expertise/prudence, accountabil ity/responsibility, sustainability, and transparency). Each principle included e xamples of ethical challenges that users might encounter when using AI for smile design.On the first round of the e-Delphi exercise, participants agreed that s even items should be considered in smile design (diversity, transparency, wellne ss, privacy protection, prudence, law and governance, and sustainable developmen t), but the remaining four items (equity, accountability and responsibility, sol idarity, and respect of autonomy) were rejected and had to be reformulated. Afte r a second round, participants agreed to all items that should be considered whi le using AI for smile design.”
      原文链接:
    • NETL
    • NSTL

    Reports from DePaul University Describe Recent Advances in Robotics (Tumbling Lo comotion of Tetrahedral Soft-limbed Robots)

    92-93页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics have been pr esented. According to news reporting originating in Chicago, Illinois, by NewsRx journalists, research stated, “Soft robots, known for their compliance and defo rmable nature, have emerged as a transformative field, giving rise to various pr ototypes and locomotion capabilities. Despite continued research efforts that ha ve shown significant promise, the quest for energyefficient mobility in soft-li mbed robots remains relatively elusive.” Financial support for this research came from National Science Foundation (NSF).
      原文链接:
    • NETL
    • NSTL

    Researcher from National Research Council of Canada Provides Details of New Stud ies and Findings in the Area of Machine Learning (Estimation of instantaneous pe ak flows in Canadian rivers: an evaluation of conventional, nonlinear regression , ...)

    93-94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 new report. According to news reporting out of Ottawa, Can ada, by NewsRx editors, research stated, “Instantaneous peak flows (IPFs) are of ten required to derive design values for sizing various hydraulic structures, su ch as culverts, bridges, and small dams/levees, in addition to informing several water resources management-related activities.” Our news journalists obtained a quote from the research from National Research C ouncil of Canada: “Compared to mean daily flows (MDFs), which represent averaged flows over a period of 24 h, information on IPFs is often missing or unavailabl e in instrumental records. In this study, conventional methods for estimating IP Fs from MDFs are evaluated and new methods based on the nonlinear regression fra mework and machine learning architectures are proposed and evaluated using strea mflow records from all Canadian hydrometric stations with natural and regulated flow regimes. Based on a robust model selection criterion, it was found that mul tiple methods are suitable for estimating IPFs from MDFs, which precludes the id ea of a single universal method. The performance of machine learning-based metho ds was also found reasonable compared to conventional and regression-based metho ds.”
      原文链接:
    • NETL
    • NSTL