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 Ma chine Learning. According to news reporting originating from Fujian, People’s Re public of China, by NewsRx correspondents, research stated, “Given the time-cons uming nature of compiling landslide inventories, it is increasingly important to develop transferable landslide susceptibility models that can be applied to reg ions without existing data. In this study, we propose a feature-based domain ada ptation method to improve the transferability of landslide susceptibility models , especially in ‘no sample’ areas.” Funders for this research include National Natural Science Foundation of China ( NSFC), Fuzhou University Testing Fund of Precious Apparatus.
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 originating in Granad a, Spain, by NewsRx journalists, research stated, “Explainable artificial intell igence is becoming increasingly important in new artificial intelligence develop ments since it enables users to understand and consequently trust system output. In the field of recommender systems, explanation is necessary not only for such understanding and trust but also because if users understand why the system is making certain suggestions, they are more likely to consume the recommended prod uct.”
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 originating in Vienna , Austria, by NewsRx journalists, research stated, “Decentralized Federated Lear ning (FL) offers a paradigm where independent entities collaboratively train a m achine learning model while preserving the privacy of their datasets. Integratin g blockchain technology into decentralized FL frameworks is critical to establis hing the trust necessary for user participation.” Financial support for this research came from ASPIRE under the ASPIRE Virtual Re search Institute Program.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Shanghai, People’s R epublic of China, by NewsRx journalists, research stated, “We apply machine-lear ning techniques to the effective-field-theory analysis of the e(+)e(-) -> W+W- processes at future lepton colliders, and demonstrate their advantages in comparison with conventional methods, such as optimal observables.” Funders for this research include National Natural Science Foundation of China ( NSFC), United States Department of Energy (DOE).
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 originating from Utrecht, Nethe rlands, by NewsRx correspondents, research stated, “We introduce a machine learn ing model designed to rapidly and accurately predict the time domain gravitation al wave emission of nonprecessing binary black hole coalescences, incorporating the effects of higher order modes of the multipole expansion of the waveform. Ex panding on our prior work [Phys. Rev.” Funders for this research include Netherlands Organization for Scientific Resear ch (NWO), National Science Foundation (NSF), Centre National de la Recherche Sci entifique (CNRS), Italian Istituto Nazionale della Fisica Nucleare (INFN), Nikhe f Theory Group, Polish and Hungarian institutes.
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 originating from Beijing, P eople’s Republic of China, by NewsRx correspondents, research stated, “This pape r studies large-scale optimization problems on Riemannian manifolds whose object ive function is a finite sum of negative log-probability losses. Such problems a rise in various machine learning and signal processing applications.”
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 Ma chine Learning. According to news reporting originating in Tampa, Florida, by Ne wsRx journalists, research stated, “Cascading failures pose a significant threat to power grids and have garnered considerable research interest in the power sy stem domain. The inherent uncertainty and severe impact associated with cascadin g failures have raised concerns, prompting the development of various techniques to study these complex phenomena.” Financial support for this research came from National Science Foundation (NSF).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on artificial intelligence are discussed in a new report. According to news reporting out of Al Ahsa, Saudi Ara bia, by NewsRx editors, research stated, “Worldwide, environmental groups and po licymakers are focusing on waste recycling to create economic value and on the d ecomposition of waste by leveraging on scarce resources.” Funders for this research include Deanship of Scientific Research (Dsr), Vice Pr esidency For Graduate Studies And Scientific Research At King Faisal University, Saudi Arabia.
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 robotics have been published. According to news originating from Hanyang University by NewsRx correspondents, research stated, “The mobile robot market is experiencing rapid growth, playing a pivotal role in various human-centric environments like resta urants, offices, hotels, hospitals, apartments, and factories.” Financial supporters for this research include Hd Hyundai Robotics.
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 from Guangdong, People’s Repu blic of China, by NewsRx journalists, research stated, “Screening high-risk popu lations is crucial for the prevention and treatment of kidney stones. Here, we e mployed radiomics to screen high-risk patients for kidney stones.” The news correspondents obtained a quote from the research from Guangzhou Medica l University, “A total of 513 independent kidneys from our hospital between 2020 and 2022 were randomly allocated to training and validation sets at a 7:3 ratio . Radiomic features were extracted using 3Dslicer software. The least absolute s hrinkage and selection operator (LASSO) method was used to select radiomic featu res from the 107 extracted features, and logistic regression, decision tree, Ada Boost, and support vector machine (SVM) models were subsequently used to constru ct radiomic feature prediction models. Among these, the logistic regression algo rithm demonstrated the best predictive performance and stability. The area under the curve (AUC) of the logistic regression model based on radiomic features was 0.858 in the training cohort and 0.806 in the validation cohort. Furthermore, u nivariate and multivariate logistic regression analyses were performed to identi fy the independent risk factors for kidney stones, which were gender and body ma ss index (BMI). Combining these independent risk factors improved the predictive performance of the model, with AUC values of 0.860 in the training cohort and 0 .814 in the validation cohort. Clinical decision curve analysis (DCA) indicated that the radiomic model provided clinical benefit when the probability ranged fr om 0.2 to 1.0.”
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