查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning have be en published. According to news originating from Mumbai, India, by NewsRx corres pondents, research stated, “Solid-state storage is a promising way to store hydr ogen due to its high energy density. However, the development of a solid-state s torage system is a complex problem due to various parameters affecting the syste ms.” Financial supporters for this research include Department of Science & Technology (India), Department of Science & Technology (India).
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 originating from Lincoln, N ebraska, by NewsRx correspondents, research stated, “Crop nitrogen (N) content r eflects crop nutrient status and plays an important role in precision nutrient m anagement. Accurate crop N content estimation from remote sensing has been well documented.” The news journalists obtained a quote from the research from University of Nebra ska-Lincoln: “However, the robustness (i.e., the ability of a model to perform c onsistently across various conditions) of these methods under varied soil condit ions or different growth stages has rarely been considered. We proposed a hybrid method that integrates in-situ measurements and the data simulated by a mechani stic model to improve the estimation of maize N content. In-situ data included h yperspectral images collected by Unmanned Aerial Vehicle (UAV), and leaf and can opy N content (LNC and CNC). A mechanistic radiative transfer model (PROSAIL-PRO ) was used to generate simulated data, i.e., canopy reflectance paired with targ et crop traits (i.e., LNC, CNC). We compared the performance from the hybrid met hod with a machine learning method (Gaussian Process Regression) and six differe nt vegetation indices (VIs) on four in-situ datasets collected at three study si tes from 2021 to 2022. Results show that the hybrid method consistently performe d the best for LNC estimation across four testing datasets (RRMSE ranging from 1 0.08% to 10.84%). For CNC estimation, the hybrid meth od had the best estimation results on two out of the four testing datasets and p erformed comparably to the best method on the other two datasets (RRMSE ranging from 13.89% to 25.21%). Next, we assessed the estimat ion robustness of the hybrid method, the machine learning, and the best-VI by co mparing the mean () and standard deviation (s) of RRMSE across diverse water and N treatments (condition #1) and different growth stages (condition #2). Among 16 total cases (two crop traits by four study sites by two conditions), the hybrid method had 11 cases of smallest and seven cases of s mallest s, outperforming the machine learning (0/16 for , 4/16 for s) and the be st-VI (5/16 for , 5/16 for s). These results underscore the greater robustness o f the hybrid method.”
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 Coimbatore, India, by NewsRx editors, research stated, “Traditional packaging industries that lack automation often g rapple with a spectrum of challenges that impede operational efficiency, product ivity and overall competitiveness. To maintain quality and safety, the food indu stry must transition from manual to robotic packaging processes.” Financial support for this research came from Ministry of Science & ICT (MSIT), Republic of Korea.
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 Translation h ave been presented. According to news reporting from Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “Autoregressive (AR) and Non- autoregressive (NAR) models are two types of generative models for Neural Machin e Translation (NMT). AR models predict tokens in a word-by-word manner and can e ffectively capture the distribution of real translations.” Financial support for this research came from National Key Ramp;D Program of Chi na.
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 - In telligent Systems have been presented. According to news reporting originating f rom Huludao, People’s Republic of China, by NewsRx correspondents, research stat ed, “Mitigating the impact of class imbalance datasets on classifiers poses a ch allenge to the machine learning community. Conventional classifiers do not perfo rm well as they are habitually biased toward the majority class.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Foundation of Liaoni ng Province Education Administration, PhD Startup Foundation of Liaoning Technic al University.
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 - Computational Intelligence have been published. According to news originat ing from Tianjin, People’s Republic of China, by NewsRx correspondents, research stated, “Despite the recent progress of continuous sign language recognition (C SLR), most state-of-the-art methods process input sign language videos frame by frame to predict sentences. This usually causes a heavy computational burden and is inefficient and even infeasible in real-world scenarios.” Financial support for this research came from National Key Research and Developm ent Program of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on artificial intelligence are present ed in a new report. According to news reporting originating from Democritus Univ ersity of Thrace by NewsRx correspondents, research stated, “Stroke is one of th e leading causes of long-term disabilities in motor and cognition functionality. ” Financial supporters for this research include Greece And The European Union. The news editors obtained a quote from the research from Democritus University o f Thrace: “An early and accurate prediction of rehabilitation outcomes can lead to a tailor-made treatment that can significantly improve the post-stroke qualit y of life of a person. This scoping review aimed to summarize studies that use A rtificial Intelligence (AI) for the prediction of language and cognition rehabil itation outcomes and the need to use AI in this domain. This study followed the PRISMA-ScR guidelines for two databases, Scopus and PubMed. The results, which a re measured with several metrics depending on the task, regression, or classific ation, present encouraging outcomes as they can predict the cognitive functional ity of post-stroke patients with relative precision. Among the results of the pa per are the identification of the most effective Machine Learning (ML) algorithm s, and the identification of the key factors that influence rehabilitation outco mes. The majority of studies focus on aphasia and present high performance achie ving up to 97% recall and 91.4% precision.”
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 Pittsbu rgh, Pennsylvania, by NewsRx editors, research stated, “Perhaps nowhere else in the healthcare system than in the intensive care unit environment are the challe nges to create useful models with direct time-critical clinical applications mor e relevant and the obstacles to achieving those goals more massive. Machine lear ning-based artificial intelligence (AI) techniques to define states and predict future events are commonplace activities of modern life.” Financial support for this research came from National Institutes of Health (NIH ) - USA.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Robotics have been publi shed. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “PurposeLimited by the types of sensors, the state information available for musculoskeletal robots with high ly redundant, nonlinear muscles is often incomplete, which makes the control fac e a bottleneck problem. The aim of this paper is to design a method to improve t he motion performance of musculoskeletal robots in partially observable scenario s, Funders for this research include National Natural Science Foundation of China ( NSFC), Chinese Academy of Sciences, National Natural Science Foundation of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Mental Health Diseases and Conditions - Bipolar Disorders is the subject of a report. According to new s reporting originating from Sydney, Australia, by NewsRx correspondents, resear ch stated, “Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity i n emerging mental disorders.” Our news editors obtained a quote from the research from the University of Sydne y, “Young people (N = 364) accessing early-intervention clinics underwent assess ments for chronotype, subjective sleep quality, and diffusion tensor imaging. Us ing machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity : fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep q uality or chronotype and considered predictors identified by 80% o f machine learning (ML) models as ‘important’. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressiv e and bipolar disorders). Subjective sleep quality only predicted FA in the peri hippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype em erged as an important (often top-ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus cal losum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis.”
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