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 Montreal, Canada, by NewsRx journalists, research stated, "Fault prediction in cloud environments is a critical task for ensuring the reliability and availability of cloud services. Machine learning (ML) techniques are increasingly used for this purpose due to their ability to recognize and predict patterns that may indicate potential faul ts." Financial support for this research came from Ericsson/ENCQOR-5G Senior Industri al Research Chair on Cloud and Edge Computing for 5G and Beyond. The news reporters obtained a quote from the research from Concordia University, "In this survey, we propose a taxonomy for ML-based fault prediction work, prov iding a critical overview, and evaluating the work from an algorithmic perspecti ve. This includes identifying five key requirements for fault prediction in clou ds and using them to evaluate the work. In this evaluation, we gain insight into the literature's current state and identify research directions."
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-Androi ds are discussed in a new report. According to news reporting originating from Q ingdao, People's Republic of China, by NewsRx correspondents, research stated, " With the rapid advancements in three-dimensional (3D) printing, researchers have shifted their focus towards the mechanical systems and methods used in this fie ld. While Fused Deposition Modelling (FDM) remains the dominant method, alternat ive printing methods such as Spatial 3DP (S-3DP) have emerged." Financial supporters for this research include Department of Education of Shando ng Province, Key Technology Research and Development Program of Shandong, Nation al 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-Data detailed on Machine Learning have been presented. According to news reporting out of Urbana, Illinois, by NewsRx editors, research stated, "Clusters of wave-scattering oscillators offer the abi lity to passively control wave energy in elastic continua. However, designing su ch clusters to achieve a desired wave energy pattern is a highly nontrivial task ." Funders for this research include National Science Foundation (NSF), National Sc ience Foundation (NSF), University of Illinois at Urbana-Champaign.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting from Stockholm, Sweden, by NewsRx jo urnalists, research stated, "With the recent vision of Industry 5.0, the cogniti ve capability of robots plays a crucial role in advancing proactive human-robot collaborative assembly. As a basis of the mutual empathy, the understanding of a human operator's intention has been primarily studied through the technique of human action recognition." Funders for this research include EU H2020 ODIN project, China Scholarship Counc il, H2020-Industrial Leadership.
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 out of Lubeck, Germany, by NewsRx editors, research stated, "Accurate rainfall forecasting is crucial for v arious sectors across diverse geographical regions, including Uttarakhand, Uttar Pradesh, Haryana, Punjab, Himachal Pradesh, Madhya Pradesh, Rajasthan, and the Union Territory of Delhi. This study addresses the need for precise rainfall pre dictions by bridging the gap between localized meteorological data and broader r egional influences." Financial supporters for this research include Deanship of Scientific Research, King Khalid University, Deanship of Scientific Research at King Khalid University.
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 out of Qingdao, People's Repu blic of China, by NewsRx editors, research stated, "Sea level change, a major co nsequence of climate change, presents significant threats to coastal regions and demands precise, timely forecasting for effective management and adaptation. Th is review assesses methodologies and approaches essential for developing robust machine learning (ML) models for predicting and forecasting sea level change (SL C)." Our news journalists obtained a quote from the research from the Ocean University of China, "Key findings reveal that artificial neural networks (ANNs), especia lly deep learning models and their hybrid variants, outperform traditional regre ssion and simpler ML techniques in short-term sea level anomaly prediction. Supe rvised learning approaches dominate the field, while semi-supervised methods exc el in short-term projections. Simpler models, such as regressions and support ve ctor machines perform better with sufficient training data, however, often exhib it lower accuracy in handling complex, non-linear scenarios. The selection of re levant input variables, such as atmospheric, oceanic, and geological factors, si gnificantly influences model accuracy, and the balance between training and test ing data is crucial for avoiding overfitting and underfitting. This review also clarifies the distinction between ML prediction and forecasting as used in the l iterature."
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 Shaanxi, People's Republic of China,by NewsRx correspondents, research stated, "Full-resolution depth estimation w ithin operational space of robotic arms and accurate localization of kiwifruits is very important for automated harvesting. Depth estimation is expected to be a ccurate and full-resolution while current depth estimation methods are susceptib le to depth missing due to occlusion and uneven illumination." Funders for this research include National Natural Science Foundation of China ( NSFC), Key Research and Development Program of Shaanxi, China, Open Project of K ey Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in South eastern China (Co-construction by Ministry and Province), Ministry of Agricultur e and Rural Affairs, China, National Foreign Expert Project, Ministry of Science and Technology, China.
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 the University of Florida by NewsRx journalists, research stated, "Four-dimensional scanning transmission ele ctron microscopy, coupled with a wide array of data analytics, has unveiled new insights into complex materials." Financial supporters for this research include National Science Foundation. The news editors obtained a quote from the research from University of Florida: "Here, we introduce a straightforward unsupervised machine learning approach that entails dimensionality reduction and clustering with minimal hyperparameter tu ning to semi-automatically identify unique coexisting structures in metallic all oys. Applying cepstral transformation to the original diffraction dataset improv es this process by effectively isolating phase information from potential signal ambiguity caused by sample tilt and thickness variations, commonly observed in electron diffraction patterns. In a case study of a NiTiHfAl shape memory alloy, conventional scanning transmission electron microscopy imaging struggles to acc urately identify a low-contrast precipitate at lower magnifications, posing chal lenges for microscale analyses. We find that our method efficiently separates mu ltiple coherent structures while using objective means of determining hyperparam eters."
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 originating from Victoria, Austr alia, by NewsRx correspondents, research stated, "Artificial intelligence (AI) a nd psychedelic medicines are among the most high-profile evolving disruptive inn ovations within mental healthcare in recent years. Although AI and psychedelics may not have historically shared any common ground, there exists the potential f or these subjects to combine in generating innovative mental health treatment ap proaches." Our news journalists obtained a quote from the research, "In order to inform our perspective, we conducted a scoping review of relevant literature up to late Au gust 2024 via PubMed intersecting AI with psychomedical use of psychedelics. Our perspective covers the potential application of AI in psychedelic medicine for: drug discovery and clinical trial optimization (including pharmacodynamics); st udy design; understanding psychedelic experiences; personalization of treatments ; clinical screening, delivery, and follow-up (potentially delivered via chatbot s/apps); application of psychological preparation, integration, and general ment al health support; its role in enhancing treatment via brain modulatory devices (including virtual reality and haptic suits); and the consideration of ethical a nd security safeguards. Challenges include the need for sufficient data protecti on and security, and a range of necessary ethical protections."
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 Beijing, People's Republ ic of China, by NewsRx journalists, research stated, "Infrared (IR) spectroscopy is a pivotal technique in chemical research for elucidating molecular structure s and dynamics through vibrational and rotational transitions. However, the intr icate molecular fingerprints characterized by unique vibrational and rotational patterns present substantial analytical challenges." The news correspondents obtained a quote from the research from Peking University, "Here, we present a machine learning approach employing a structural neighbor ing mechanism tailored to enhance the prediction and interpretation of infrared spectra. Our model distinguishes itself by honing in on chemical information pro ximal to functional groups, thereby significantly bolstering the accuracy, robus tness, and interpretability of spectral predictions."
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