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 originating from Alexandria, Egypt, by NewsRx correspondents, research stated, “Retained surgical items (RSIs ) pose significant risks to patients and healthcare professionals, prompting ext ensive efforts to reduce their incidence. RSIs are objects inadvertently left wi thin patients’ bodies after surgery, which can lead to severe consequences such as infections and death.” Financial support for this research came from Egypt Japan University.
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 originating from Beijing, People’s R epublic of China, by NewsRx correspondents, research stated, “The exceptional sw imming agility observed in dolphins is primarily attributed to the flexibility o f their tails. Drawing inspiration from this biological phenomenon, this letter introduces a novel dual tendon-driven robotic dolphin tail featuring a passive j oint designed to facilitate omnidirectional motion.” Financial support for this research came from National Key R&D Prog rams of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on robotics is the subjec t of a new report. According to news originating from Harbin, People’s Republic of China, by NewsRx editors, the research stated, “This study presents a novel i mage-based visual servoing fault-tolerant control strategy aimed at ensuring the successful completion of visual servoing tasks despite the presence of robotic arm actuator faults.” Financial supporters for this research include Fundamental Strengthening Program Technical Field Fund. Our news reporters obtained a quote from the research from Harbin Engineering Un iversity: “Initially, a depth-independent image-based visual servoing model is e stablished to mitigate the effects of inaccurate camera parameters and missing d epth information on the system. Additionally, a robotic arm dynamic model is con structed, which simultaneously considers both multiplicative and additive actuat or faults. Subsequently, model uncertainties, unknown disturbances, and coupled actuator faults are consolidated as centralized uncertainties, and an iterative learning fault observer is designed to estimate them.”
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 autonomous intelligence is now available. According to news reporting out of Tongji University by NewsR x editors, research stated, “Artificial intelligence empowers the rapid developm ent of autonomous intelligent systems (AISs), but it still struggles to cope wit h open, complex, dynamic, and uncertain environments, limiting its large-scale i ndustrial application.” Financial supporters for this research include National Natural Science Foundati on of China.
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 reporting originating in Austin, Texas, by NewsRx jo urnalists, research stated, “In this paper, we propose a novel biomechanicsawar e robot-assisted steerable drilling framework with the goal of addressing common complications of spinal fixation procedures occurring due to the rigidity of dr illing instruments and implants.” Financial support for this research came from National Institutes of Health (NIH ) - USA. The news reporters obtained a quote from the research from the University of Tex as Austin, “This framework is composed of two main unique modules to design a ro botic system including (i) a Patient- Specific Biomechanics-aware Trajectory Sele ction Module used to analyze the stress and strain distribution along an implant ed pedicle screw in a generic drilling trajectory (linear and/or curved) and obt ain an optimal trajectory; and (ii) a complementary semi-autonomous robotic dril ling module that consists of a novel Concentric Tube Steerable Drilling Robot (C T-SDR) integrated with a seven degree-of-freedom robotic manipulator. This semi- autonomous robot-assisted steerable drilling system follows a multi-step drillin g procedure to accurately and reliably execute the optimal hybrid drilling traje ctory (HDT) obtained by the Trajectory Selection Module.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news reporting out of Helwan, Egypt, by New sRx editors, research stated, “An earthquake early-warning system (EEWS) is an i ndispensable tool for mitigating loss of life caused by earthquakes. The ability to rapidly assess the severity of an earthquake is crucial for effectively mana ging earthquake disasters and implementing successful risk-reduction strategies. ” Our news journalists obtained a quote from the research from National Research I nstitute of Astronomy and Geophysics: “In this regard, the utilization of an Int ernet of Things (IoT) network enables the realtime transmission of on-site inte nsity measurements. This paper introduces a novel approach based on machine-lear ning (ML) techniques to accurately and promptly determine earthquake intensity b y analyzing the seismic activity 2 s after the onset of the p-wave. The proposed model, referred to as 2S1C1S, leverages data from a single station and a single component to evaluate earthquake intensity. The dataset employed in this study, named “INSTANCE,” comprises data from the Italian National Seismic Network (INS N) via hundreds of stations. The model has been trained on a substantial dataset of 50,000 instances, which corresponds to 150,000 seismic windows of 2 s each, encompassing 3C. By effectively capturing key features from the waveform traces, the proposed model provides a reliable estimation of earthquake intensity, achi eving an impressive accuracy rate of 99.05% in forecasting based o n any single component from the 3C.”
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 Ar tificial Intelligence. According to news reporting from Zhengzhou, People’s Repu blic of China, by NewsRx editors, the research stated, “We have carried out mode ling and computation of mass transfer in a membrane contactor for removal of org anic compounds from aqueous solutions. Both computational fluid dynamics (CFD) a nd Artificial Intelligence (AI) methods were utilized for modeling separation pr ocess.” The news correspondents obtained a quote from the research from Henan Finance Un iversity, “For the AI, we explored the application of three distinct regression models, namely Kernel Ridge Regression, Gaussian Process Regression, and Poisson Regression to predict the concentration of a component, C, based on r and z. To enhance the performance of these models, the hyper-parameter tuning process emp loys Glowworm Swarm Optimization (GSO). The findings illustrate the effectivenes s of the utilized models. Gaussian Process Regression achieves a noteworthy R2 s core of 0.99791, with a RMSE of 3.9666 x 101(mol/m3) and an AARD% of 4.52000 x 10-1. Kernel Ridge Regression, while slightly less accurate, achiev es a commendable R2 value of 0.97865, with an RMSE of 1.2446 x 102(mol/m3) and a n AARD% of 2.63808. Poisson Regression offers a respectable perfor mance, yielding an R2 score of 0.95509, along with an RMSE of 1.8011 x 102(mol/m 3) and an AARD% of 4.28969.”
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 reporting out of Manchester, Uni ted Kingdom, by NewsRx editors, research stated, “The sinus node (SN) serves as the primary pacemaker of the heart and is the first component of the cardiac con duction system. Due to its anatomical properties and sample scarcity, the cellul ar composition of the human SN has been historically challenging to study.” Funders for this research include British Heart Foundation, Fondation Leducq.
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 Learning. According to news reporting from Grand Forks, North Dakota, by NewsRx journalists, research stated, “Modifying reverse-osmosis (RO) membrane performa nce is challenging and time-consuming due to the complex interplay of various fa ctors that influence the membrane’s performance. To address this challenge, we h ave explored the potential of using machine-learning (ML) to graft the polyamide (PA) surface of an RO membrane to increase water permeability and overcome the limitations of the permeability/selectivity tradeoff.” Financial supporters for this research include City of Grand Forks, State of Nor th Dakota, American Membrane Technology Association (AMTA), United States Bureau of Reclamation.
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 originating from Odisha, India, by NewsRx cor respondents, research stated, “Advancing industrialization has led to an exponen tial degradation of consumable water, and hence, there is a direct need for an e fficient monitoring system. In this study, we demonstrated hierarchical, nanostr uctured Ni2O3- and Cu0.05Ni1.95O3-based resistive bisensor arrays for selective detection of Zn(II) ions in solution.” Financial support for this research came from Science and Engineering Research B oard (SERB) through the Government of India.
NETL
NSTL