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 originating from Taiyuan, People's Repu blic of China, by NewsRx correspondents, research stated, "Garnet solid-state el ectrolytes have become one of the most promising electrolyte materials due to th eir high ionic conductivity, wide electrochemical window, and excellent electroc hemical stability. However, the trialand -error method used to screen high-perfo rmance garnet solid-state electrolytes has the disadvantages of a long developme nt cycle and high cost." Funders for this research include National Natural Science Foundation of China ( NSFC), Key Research and Development Program of Shanxi Province, Central Governme nt Guides Local Science, Technology Development Special Fund Project, Key R& D program of Shanxi Province.
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 originating from Binghamton, New York, by NewsRx correspondents, research stated, "Robots present an opportunity to enh ance healthcare delivery. Rather than targeting complete automation and nurse re placement, collaborative robots, or ‘cobots', might be designed to allow nurses to focus on high-value caregiving." The news correspondents obtained a quote from the research from State University of New York (SUNY) Binghamton: "While many institutions are now investing in th ese platforms, there is little publicly available data on how cobots are being d eveloped, implemented, and evaluated to determine if and how they support nursin g practice in the real world. This systematic review investigates the current st ate of cobotic technologies designed to assist nurses in hospital settings, thei r intended applications, and impacts on nurses and patient care. A comprehensive database search identified 28 relevant peer-reviewed articles published since 2 018 which involve real studies with robotic platforms in simulated or actual cli nical contexts. Few cobots were explicitly designed to reduce nursing workload t hrough administrative or logistical assistance. Most included studies were desig ned as patient-centered rather than nursecentered, but included assistance for tasks like medication delivery, vital monitoring, and social interaction. Most a pplications emerged from India, with limited evidence from the United States des pite commercial availability of nurse-assistive cobots. Robots ranged from proof -of-concept to commercially deployed systems."
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 reportin g out of Geelong, Australia, by NewsRx editors, research stated, "Video super-re solution (VSR) is a prominent research topic in low-level computer vision, where deep learning technologies have played a significant role. The rapid progress i n deep learning and its applications in VSR has led to a proliferation of tools and techniques in the literature." Financial support for this research came from Air Force Office of Scientific Res earch (AFOSR).
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 Hangzhou, Peopl e's Republic of China, by NewsRx journalists, research stated, "This study aims to examine design students' intention towards using Artificial Intelligence-aide d Design Tools (AIDTs). An extended model is developed by combining the affectiv e-cognitive consistency theory with the Unified Theory of Acceptance and Use of Technology (UTAUT)." Funders for this research include National Key Research and Development Program of China, National key research and development program of China.
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 - Intelligent Systems. According to news reporting out of Hefei, People's Republic of China, by NewsRx editors, research stated, "In recent years , the applications of digital humans have become increasingly widespread. One of the most challenging core technologies is the generation of highly realistic an d automated 3D facial animation that combines facial movements and speech." Financial support for this research came from The National Key Research and Deve lopment Program of China.
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 Ames, Iowa, by NewsRx editors, research stated, "We employ deep machine learning (ML) combined with first-principles calculations to explore energetically favorable ternary m etal borohydrides. Using La-B-H as a prototype system, we demonstrate that itera tively trained ML models can efficiently screen hundreds of thousands of hypothe tical structures and accurately select a small fraction of promising structures and compositions for further studies by first-principles calculations." Funders for this research include Natural Science Foundation of Shandong Provinc e, United States Department of Energy (DOE), United States Department of Energy (DOE), Natural Science Foundation of Shandong Province.
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 Jiangsu, People's Republic of China, by NewsRx editors, research stated, "Human gait pattern recognition and complian ce control are key technologies for achieving high coordination and assistance b etween exoskeleton robots and human movements." Our news reporters obtained a quote from the research from Southeast University: "In order to improve the adaptability of exoskeleton robots to the human body, this paper proposes an exoskeleton compliance control strategy based on dual int eraction torque phase separation control method. A support phase swing phase spl it control strategy based on dual interaction torque is proposed. Utilize the in teraction force of human joints and adopt a model-based method to control the su pport phase. By utilizing the interaction force of exoskeleton joints and using a torque closed-loop method to control the swing phase, a multi-state control me thod of motion is achieved. A lower limb exoskeleton knee joint testing platform is built to verify the proposed human gait recognition The effectiveness of hum an-machine interaction force identification and human-machine coupling system co mpliance control technology."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Esophageal Cancer is the subject of a report. According to news reporting originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, "To investigate the feasibility and accuracy of predicting locoregional recurre nce (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who und erwent radical radiotherapy using a pairwise machine learning algorithm. The 130 datasets enrolled were randomly divided into a training set and a testing set i n a 7:3 ratio." Funders for this research include Natural Science Foundation of Hebei Province, Hebei Provincial Department of Science and Technology.
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 Machine Learning is now available. According to news reporting out of New York City, New York, by NewsR x editors, research stated, "The recent rapid advancements in both sensing and m achine learning technologies have given rise to the universal collection and uti lization of people's biometrics, such as fingerprints, voices, retina/facial sca ns, or gait/motion/gestures data, enabling a wide range of applications includin g authentication, health monitoring, or much more sophisticated analytics. While providing better user experiences and deeper business insights, the use of biom etrics has raised serious privacy concerns due to their intrinsic sensitive natu re and the accompanying high risk of leaking sensitive information such as ident ity or medical conditions." Financial support for this research came from European Commission Joint Research Centre.
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 from Hang zhou, People's Republic of China, by NewsRx correspondents, research stated, "Th e incessant decrease in transistor size has led to reduced voltage noise margins and exacerbated power integrity challenges. This trend intensifies concerns abo ut the efficacy of conventional static timing analysis (STA), which traditionall y assumes a constant power supply level, often resulting in imprecise and overly conservative outcomes." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from Zhejiang University, "T o address this, this article proposes a dynamic-noise-aware STA engine enhanced by just-in-time (JIT) machine learning (ML) integration. This approach employs t he Weibull cumulative distribution function (CDF) to accurately represent dynami c power supply noise (PSN). We perform gate-level characterization, assessing de lay and transition time for each timing arc under variations in input transition time, output capacitance, and three PSN-aware parameters. The timing for each t iming arc can then be predicted by a multilayer perceptron (MLP), trained with t he characterization data. Finally, by incorporating JIT compilation techniques, we integrate trained MLP models into the STA engine, achieving both computationa l efficiency and flexibility."
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