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    Data on Machine Translation Reported by Researchers at Nanjing Agricultural Univ ersity (Understanding Machine Translation Fit for Language Learning: the Mediati ng Effect of Machine Translation Literacy)

    19-20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 Machine Translation. According to news reporting from Nanjing, People’s Republic of Chi na, by NewsRx editors, the research stated, “The use of machine translation has become a topic of debate in language learning, which highlights the need to thor oughly examine the appropriateness and role of machine translation in educationa l settings. Under the theoretical framework of task-technology fit, this explana tory case study set out to investigate the predictive role of machine translatio n fit, based on questionnaire responses obtained from a sample of 500 Chinese un iversity EFL learners.”
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    Study Findings on Machine Learning Detailed by Researchers at Hangzhou Dianzi Un iversity (Class imbalance: A crucial factor affecting the performance of tea pla ntations mapping by machine learning)

    20-21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 artificial intell igence are discussed in a new report. According to news reporting out of Hangzho u, People’s Republic of China, by NewsRx editors, research stated, “Due to dispa rities in area among various land cover types, class imbalance has always existe d in crop mapping research, posing uncertainties in extracting minority classes which occupy a smaller area.” Financial supporters for this research include Key Research And Development Prog ram of Zhejiang Province; National Natural Science Foundation of China.
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    Study Results from Guang’anmen Hospital Provide New Insights into Artificial Int elligence (Applications of Artificial Intelligence in the Detection of Tradition al Chinese Herbal Medicines and Prepared Slices)

    21-22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 artificial intell igence are discussed in a new report. According to news reporting out of Beijing , People’s Republic of China, by NewsRx editors, research stated, “Currently, th e market demand for traditional Chinese herbal medicines and prepared slices is experiencing rapid growth, rendering quality control and safety assurance even m ore pressing issues.” The news editors obtained a quote from the research from Guang’anmen Hospital: “ Conventional testing methods for traditional Chinese herbal medicines and prepar ed slices, which are heavily reliant on subjective experience, limited in detect ion precision, and unable to comprehensively quantify complex constituents, are increasingly inadequate in satisfying the requirements for accurate classificati on, differentiation, and precise measurement of components in these materials. T he rapid development and widespread application of artificial intelligence (AI), however, offer novel solutions for the testing of the traditional Chinese herba l medicines and prepared slices. This study summarizes the existing methods and current status of testing for the traditional Chinese herbal medicines and prepa red slices, sorts out the typical applications of AI in medicinal material class ification, authenticity identification, traceability of origin, harmful ingredie nt measurement, effective ingredient measurement, and medicinal effect measureme nt, and analyzes the current problems regarding data collection and standardizat ion; sharing of testing data; demands for rapid, non-destructive, low-cost testi ng technologies; accuracy of testing data; and fusion of multi-modal testing dat a. The study believes that intelligence, precision, and speed are the key develo pment directions for the testing of the traditional Chinese herbal medicines and prepared slices.”
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    Data on Machine Learning Published by a Researcher at Barkatullah University (Mo deling and Estimation of Reference Evapotranspiration using Machine Learning Alg orithms: A Comparative Performance Analysis)

    22-23页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News - Investigators publish new report on artificial in telligence. According to news reporting from Bhopal, India, by NewsRx journalist s, research stated, “Fresh, clean water is necessary for human health. Currently , the agriculture sector uses the majority of freshwater for irrigation without using planning or optimization techniques.” Our news editors obtained a quote from the research from Barkatullah University: “Evapotranspiration, which may have a major impact in planning water supply man agement and crop yield improvement, is an element of the hydrological cycle. Acc urate anticipation of reference evapotranspiration (ETO) is an intricate job due to its nonlinear behavior. Machine learning approach based model may be an inte lligent tool to predict the accurate ETO. This study investigates and compares t he predictive skills of three regression based supervised learning algorithms: d ecision tree (dtr), and random forest (rfr), and k-nearest-neighbors (knnr) alon g with tuning their hyper-parameters like how many neighbors there are in knnr, minimum samples in dtr at a leaf node and quantity of trees in the rfr scenario to forecast ETO. Every model’s performance is quantified on four different group s of meteorological parameters. Groups are created based on close correlation of meteorological parameters with ETo. In this investigation, analysis is carried out on daily meteorological information of New Delhi, India for the periods from 2000 to 2021. The predicted results of the knnr, dtr and rfr models on four gro ups of meteorological inputs (twelve different models) are compared with ETO obt ained from the FAO-PM56 equations.”
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    Studies from Beijing Electronic Science and Technology Institute Add New Finding s in the Area of Machine Learning (A personalized federated learning method base d on the residual multi-head attention mechanism)

    23-23页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - A new study on artificial intelligence is now available. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Federated Learning (FL) i s a distributed machine learning technique for training machine learning models across multiple clients collaboratively. It allows multiple local devices to coo peratively train global models without compromising data privacy or necessitatin g extensive data transfer.” Financial supporters for this research include Beijing Electronic Science And Te chnology Institute; Fundamental Research Funds For The Central Universities.
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    New Findings from University of Oklahoma Describe Advances in Machine Learning ( Uncertainty Assessment in Unsupervised Machine Learning Methods For Deepwater Ch annel Seismic Facies Using Outcrop-derived 3D Models And Synthetic Seismic Data)

    24-24页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - A new study on artificial intelligence is now available. According to news originating from Norman, Oklahoma, by NewsR x correspondents, research stated, “Unsupervised machine learning (ML) technique s have been widely applied to analyze seismic reflection data, including the ide ntification of seismic facies and structural features.” The news editors obtained a quote from the research from University of Oklahoma: “However, interpreting the resulting clusters often relies on geoscientists’ ex pertise, necessitating a robustness assessment of these methods. To evaluate the ir reliability, synthetic data generated from an actual outcrop model were emplo yed to demonstrate how two unsupervised methods, Self-Organizing Maps (SOM) and Generative Topographic Maps (GTM), cluster deepwater channel-related seismic fac ies and then measure the associated error. Six seismic attributes, comprising RM S amplitude, instantaneous envelope, peak magnitude, and spectral decomposition frequencies at 20, 40, and 55 Hz, served as input variables. Geobodies were assi gned to each cluster formed, and error in facies clustering was quantified by co mparing the actual 3D model with the facies grouped by machine learning methods on a voxel-by-voxel basis. This allowed for error quantification and the computa tion of metrics such as F1 score and accuracy through correlation matrices. Key findings revealed that (1) GTM and SOM exhibited similar performance, with a clu stering configuration of 81 for GTM slightly outperforming others.”
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    Recent Findings in Artificial Intelligence Described by Researchers from Emory U niversity (Effects of Explainable Artificial Intelligence In Neurology Decision Support)

    25-25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 from Atlanta, Georgi a, by NewsRx journalists, research stated, “Artificial intelligence (AI)-based d ecision support systems (DSS) are utilized in medicine but underlying decision-m aking processes are usually unknown. Explainable AI (xAI) techniques provide ins ight into DSS, but little is known on how to design xAI for clinicians.” Financial support for this research came from National Institutes of Health (NIH ) - USA.
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    Studies Conducted at University of Lisbon on Artificial Intelligence Recently Re ported (Music and Affectivity In the Age of Artificial Intelligence)

    26-26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 out of Lisbon, Portugal, by NewsRx editors, the research stated, “Music and affects share a long history. I n recent times, 4E cognitive sciences (embodied, embedded, enacted, and extended ), situated affectivity, and related ecological theoretical frameworks have been conceptualizing music as a case of a tool for feeling.”
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    New Findings Reported from Chengdu University of Technology Describe Advances in Artificial Intelligence (Applicability of denoisingbased artificial intelligen ce to forecast the environmental externalities)

    26-27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 artificial intell igence are discussed in a new report. According to news reporting from Chengdu U niversity of Technology by NewsRx journalists, research stated, “The current stu dy attempts to compare the hybrid artificial intelligence models to forecast the environmental externalities in Saudi Arabia. We have used the denoising based a rtificial intelligence models to construct hybrid models.”
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    Investigators at Department of Computer Sciences Describe Findings in Machine Le arning (A Machine Learning Approach for Anomaly Detection On the Internet of Thi ngs Based On Localitysensitive Hashing)

    27-28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 Machine Learning are pre sented in a new report. According to news reporting originating from Puebla, Mex ico, by NewsRx correspondents, research stated, “The increasing connectivity of devices on the Internet of Things (IoT) has created a favorable field for attack s. Consequently, current anomaly-based intrusion detection systems (AIDS) integr ate artificial intelligence algorithms, such as machine learning (ML) and deep l earning (DL), to manage high data volumes, recognize complex patterns, and detec t unknown anomalies.”
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