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 from Jiangsu, People's Republi c of China, by NewsRx correspondents, research stated, "The dual-robotic ultraso nic nondestructive testing (NDT) system equipped with extension arm is an effect ive means to realize automatic ultrasonic testing of composite semi-enclosed wor kpieces." Financial supporters for this research include Qing Lan Project And 333 Project of Jiangsu Province; Natural Science Foundation of The Jiangsu Higher Education Institutions of China; National Natural Science Foundation of China; Independent Innovation Fund of Jiangsu Agricultural Committee; Key R & D Plan of Jiangsu Province. The news editors obtained a quote from the research from Jiangsu University: "Ho wever, this cantilever structure amplifies the tiny vibrations of the inspection system, which seriously affects the coupling effect and the resolution of ultra sonic inspection. To solve the problem, this paper proposes a S-shaped accelerat ion and deceleration feature control algorithm to improve the motion stability a nd further to improve the inspection resolution of dual-robotic ultrasonic NDT s ystem. Furthermore, the specific steps of S-shaped acceleration and deceleration features control algorithm in trajectory planning of the dual-robotic ultrasoni c NDT system are described in detail."
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 Robotic s. According to news reporting out of Shenyang, People's Republic of China, by N ewsRx editors, research stated, "It has been widely reported that untethered mic ro -robots can access hard-to-reach regions within the body to perform a range o f medical procedures. However, the narrow operating space limits the ability of such microrobots to interact with the external environment." Financial supporters for this research include National Key R & D Program of China, National Natural Science Foundation of China (NSFC), Innovatio n Promotion Research Association of the Chinese Academy of Sciences.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New study results on artificial intelligence have been published. According to news originating from Volos, Greece, by NewsRx cor respondents, research stated, "This study aims to develop a methodology to asses s hull fouling based on ship propulsion data such as speed, draft and weather re lated data." Our news editors obtained a quote from the research from University of Thessaly: "Hull fouling is an unavoidable phenomenon in ships and results in higher fuel consumption and the maintenance frequency has be the optimal one. Despite the fa ct that until now this task has primarily relied on empirical rules, it turns ou t that it can be improved by employing machine learning techniques. Using data f rom clean-hull ships, we aim to isolate and consider only the weather in this st udy. Our goal is to replace empirical rules with machine learning, as the vast a mount of data we possess can significantly aid us in this endeavor. It ends up t o be a regression problem, and therefore, we experiment with several supervised algorithms using k-fold cross validation to finally select models based on ensem ble methods or artificial neural networks. We propose the potential use of MLP R egressor, Random Forest Regressor and XGB Regressor since all of them yielded ve ry good results in terms of some performance metrics."
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 originating from Pittsburgh, Pennsylvania , by NewsRx correspondents, research stated, "To develop a machine learning algo rithm, using patient-reported data from early pregnancy, to predict later onset of first time moderate-to-severe depression.Methods A sample of 944 U.S. patient participants from a larger longitudinal observational cohortused a prenatal sup port mobile app from September 2019 to April 2022. Participants self-reported cl inical and social risk factors during first trimester initiation of app use and completed voluntary depression screenings in each trimester." Financial support for this research came from NIH National Institute of Mental H ealth (NIMH).
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 Roskilde, Denma rk, by NewsRx editors, research stated, "Plankton is essential to maintain healt hy aquatic ecosystems since it influences the biological carbon pump globally. H owever, climate change-induced alterations to oceanic properties threaten plankt onic communities." Our news journalists obtained a quote from the research from the Technical Unive rsity of Denmark (DTU), "It is therefore crucial to monitor their abundance to a ssess the health status of marine ecosystems. In situ optical tools unlock high- resolution measurements of sub-millimeter specimens, but state-of-theart underw ater imaging techniques are limited to fixed and small close-range volumes, requ iring the instruments to be vertically dived. Here, a novel scanning multispectr al confocal light detection and ranging (LiDAR) system for short-range volumetri c sensing in aquatic media is introduced. The system expands the inelastic confo cal principle to multiple wavelength channels, allowing the acquisition of 4D po int clouds combining near-diffraction limited morphological and spectroscopic da ta that is used to train artificial intelligence (AI) models. Volumetric mapping and classification of microplastics is demonstrated to sort them by color and s ize. Furthermore, in vivo autofluorescence is resolved from a community of free- swimming zooplankton and microalgae, and accurate spectral identification of dif ferent genera is accomplished. The deployment of this photonic platform alongsid e AI models overcomes the complex and subjective task of manual plankton identif ication and enables non-intrusive sensing from fixed vantage points, thus consti tuting a unique tool for underwater environmental monitoring. A novel multispect ral confocal light detection and imaging (LiDAR) system for underwater autofluor escence short-range sensing is introduced. The instrument combines 3D high-resol ution morphological data with spectroscopic information at the voxel level."
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 Chandigarh , India, by NewsRx editors, the research stated, "Machine learning based statist ical models have played a significant role in increasing the speed and accuracy with which the chemical and physical properties of chemical compounds can be pre dicted as compared to the experimental, and traditional ab initio and quantum me chanical approaches. The transformative impact that these techniques have, in th e field of chemical sciences has completely changed the way experiments are desi gned." Financial support for this research came from 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-New research on Surgery - Nephrectomy is the subject of a report. According to news reporting originating from Mannhei m, Germany, by NewsRx correspondents, research stated, "To comprehensively compa re quality-of-life (QoL) outcomes between open partial nephrectomy (OPN) and rob ot-assisted PN (RAPN) from the randomised ROBOtic-assisted versus Conventional O pen Partial nephrectomy (ROBOCOP) II trial, as QoL data comparing OPN and RAPN a re virtually non-existent, especially not from randomised controlled trials (RCT s). The ROBOCOP II was a single-centre, open-label RCT between OPN and RAPN." Financial support for this research came from Dietmar Hopp Stiftung.
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 from Shenzhen, People's Republic of China, by NewsRx journalists, research stated, "This article investigates one of the m ost challenging tasks in dynamic manipulation-catching large-momentum moving obj ects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with it s surrounding environment." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from the Harbin Insti tute of Technology, "Yet, the inevitable motion mismatch between the fast moving object and the approaching robot will result in large impulsive forces, which l ead to the unstable contacts and irreversible damage to both the object and the robot. To address the above problems, we propose an online optimization framewor k to: 1) estimate and predict the linear and angular motion of the object, 2) se arch and select the optimal contact locations across every surface of the object to mitigate impact through sequential quadratic programming, 3) simultaneously optimize the end-effector motion, stiffness, and contact force for both robots u sing multimode trajectory optimization (MMTO), and 4) realise the impact-aware c atching motion on the compliant robotic system based on indirect force controlle r."
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 Shanghai, People's Republic of China, by NewsRx correspondents, research stated, "Performance -base d earthquake engineering (PBEE) has asserted probabilistic seismic fragility ass essment (PSFA) as the main research content in light of its irreplaceable signif icance for seismic decision -making in recent decades. Among the multiple approa ches of PSFA implementation, the classical linear regression method (LRM) domina tes over practice regarded as one of the most widely -used." Funders for this research include National Key R&D Program of China , National Natural Science Foundation of China (NSFC). Our news editors obtained a quote from the research from Tongji University, "How ever, the general LRM adopts quantile regression method (QRM) on the group of fr agility curves to approximate a deterministic probability density distribution ( PSD) of structural fragility against certain intensity measure (IM) of potential ly confronting earthquake. Consequently, the QRM-derived fragility representatio n might not be credible enough while evaluating a newly -occurred seismic event owing to its neglect of specificity of stochastic ground motion. To address this issue, a fusing physics -based and machine learning models towards rapid ground -motion-adaptative probabilistic seismic fragility assessment (GmaPSFA) is propo sed in present study. With sophisticated framework design and novel fragility hy perparameters estimation, the involved design philosophy and mechanism translati ng are both elaborated. To validate the method, both the LRM and GmaPSFA were co nducted on a six -story frame structure, where a novel fully -automatic batch pr ocessing approach fusing APDL and coding languages was propounded for structural analysis."
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 Krakow, Poland, by N ewsRx editors, research stated, "One of the challenges in managing cloud computi ng clusters is assigning resources based on the customers' needs. For this mecha nism to work efficiently, it is imperative that there are sufficient resources r eserved to maintain continuous operation, but not too much to avoid overhead cos ts." Financial supporters for this research include Ministerstwo Edukacji i Nauki, Mi nistry of Science and Higher Education, Poland, AGH University of Krakow.
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