查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on robotics have bee n published. According to news originating from Lianyungang, People’s Republic o f China, by NewsRx editors, the research stated, “Robot technology shows broad a pplication prospects in rehabilitation medicine, especially in hand rehabilitati on. Hand function plays an important role that cannot be ignored in daily life, and its key properties are reflected in multiple levels.” The news editors obtained a quote from the research from Nanjing Medical Univers ity: “From basic life skills to occupational needs, healthy hand function is ind ispensable. Hand function is the foundation for performing daily life skills, in cluding activities such as self-care, eating, dressing, and grooming. The abilit y to freely use hand functions is directly related to an individual’s quality of life and independence. This study proposed a gesture recognition algorithm by f using Ycbcr color space and convolutional neural network. The method first conve rted gesture images and recognizes them through the converted images. Then, a ha nd function rehabilitation training robot based on Ycbcr and CNN was designed, w hich provided rehabilitation treatment for patients with impaired hand function. These experiments confirmed that when the data set size was 500, the signal-to- noise ratios of YOLOV3, YOLOV3-SPP, YOLOV4, and hybrid algorithms were 27.5dB, 3 2.7dB, 34.8dB, and 41.2dB, respectively.”
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 Robotics - Robotics and Automation is now available. According to news reporting originating in Cambrid ge, Massachusetts, by NewsRx journalists, research stated, “Imitation learning ( IL) can train computationally-efficient sensorimotor policies from a resource-in tensive model predictive controller (MPC), but it often requires many samples, l eading to long training times or limited robustness. To address these issues, we combine IL with a variant of robust MPC that accounts for process and sensing u ncertainties, and we design a data augmentation (DA) strategy that enables effic ient learning of vision-based policies.” Financial support for this research came from MURI. The news reporters obtained a quote from the research from the Massachusetts Ins titute of Technology, “The proposed DA method, named Tube-NeRF, leverages Neural Radiance Fields (NeRFs) to generate novel synthetic images, and uses properties of the robust MPC (the tube) to select relevant views and to efficiently comput e the corresponding actions. We tailor our approach to the task of localization and trajectory tracking on a multirotor, by learning a visuomotor policy that ge nerates control actions using images from the onboard camera as only source of h orizontal position. Numerical evaluations show 80-fold increase in demonstration efficiency and a 50% reduction in training time over current IL m ethods.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Artificial Intelligence. According to news reporting originating from Melbourne, Australia, by NewsRx correspondents, research stated, “This review article underscores the critical role of Density Functional Theory (DFT) in the prediction of corrosion defect structures based on specific chemical compositions. By integrating DFT w ith Molecular Dynamics (MD) simulations, we gain a more nuanced understanding of corrosion processes.” Funders for this research include Australian Research Council, Tuition Scholarsh ip from Swinburne University of 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 artificial intelligenc e is the subject of a new report. According to news reporting originating from O saka University by NewsRx correspondents, research stated, “Dynamic mode (DM) de composition decomposes spatiotemporal signals into basic oscillatory components (DMs).” Funders for this research include Mext | Japan Science And Technology Agency; Ja pan Agency For Medical Research And Development; Mext | Japan Society For The Pr omotion of Science. Our news correspondents obtained a quote from the research from Osaka University : “DMs can improve the accuracy of neural decoding when used with the nonlinear Grassmann kernel, compared to conventional power features. However, such kernel- based machine learning algorithms have three limitations: large computational ti me preventing real-time application, incompatibility with non-kernel algorithms, and low interpretability. Here, we propose a mapping function corresponding to the Grassmann kernel that explicitly transforms DMs into spatial DM (sDM) featur es, which can be used in any machine learning algorithm. Using electrocorticogra phic signals recorded during various movement and visual perception tasks, the s DM features were shown to improve the decoding accuracy and computational time c ompared to conventional methods. Furthermore, the components of the sDM features informative for decoding showed similar characteristics to the high-g power of the signals, but with higher trial-to-trial reproducibility.”
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 Burlington, Vermont, by NewsRx editor s, research stated, “Sensing and cognition by homeowners and technicians for hom e maintenance are prime examples of human-building interaction.” Financial supporters for this research include Broad Agency Announcement Program And Cold Regions Research And Engineering Laboratory; Office of Navy Research; Nsf; Nasa Epscor.Our news journalists obtained a quote from the research from University of Vermo nt: “Damage, decay, and pest infestation present signals that humans interpret a nd then act upon to remedy and mitigate. The maintenance cognition process has d irect effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern tech nologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recomme nd courses of remedial action. The demonstrated technologies include robotic sen sing in confined areas, LiDAR scans of structural shape and deformation, moistur e and gas sensing, water leak detection, network embedded ML, and augmented real ity interfaces with multi-user teaming capabilities.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Artificial Intelligence are presented in a new report. According to news reporting originating from Hart ford, Connecticut, by NewsRx editors, the research stated, “Artificial intellige nce has recently become available for widespread use in medicine, including the interpretation of digitized information, big data for tracking disease trends an d patterns, and clinical diagnosis. Comparative studies and expert opinion suppo rt the validity of imaging and data analysis, yet similar validation is lacking in clinical diagnosis.” Our news editors obtained a quote from the research from Hartford Hospital, “Art ificial intelligence programs are here compared with a diagnostic generator prog ram in clinical neurology. Using 4 nonrandomly selected case records from New En gland Journal of Medicine clinicopathologic conferences from 2017 to 2022, 2 art ificial intelligence programs (ChatGPT-4 and GLASS AI) were compared with a neur ological diagnostic generator program (NeurologicDx.com) for diagnostic capabili ty and accuracy and source authentication. Compared with NeurologicDx.com, the 2 AI programs showed results varying with order of key term entry and with repeat querying. The diagnostic generator yielded more differential diagnostic entitie s, with correct diagnoses in 4 of 4 test cases versus 0 of 4 for ChatGPT-4 and 1 of 4 for GLASS AI, respectively, and with authentication of diagnostic entities compared with the AI programs.”
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 report. According to news reporting originating from Vienna, Austria, by NewsRx correspondents, research stated, “The performance of postinstalled faste ners in concrete can be affected by the chosen drilling and setting techniques. In the context of the development of a drilling robot for construction site impl ementation the impact of an automated setting process on the pull-out loads of f astening systems was evaluated.” Financial support for this research came from Fischerwerke GmbH Co. Our news editors obtained a quote from the research from the University of Natur al Resources and Applied Life Science, “This article investigates the effect of two different fixing systems, drop-in expansion and chemical anchors, on the pul l-out behaviour of manual and robotic drilling and installation. While for chemi cal anchors, the results indicate that robotic installation leads to similar pul l-out forces with smaller deviation, expansion anchors in robotically drilled ho les show slightly lower pull-out loads than those in manually drilled holes. Fur thermore, a more uniform pull-out behaviour was observed for chemical anchors wh en set by the robot.”
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 reporting out of Qingdao, People’s Republic of C hina, by NewsRx editors, research stated, “Complex risk factors make metro const ruction safety accidents prone to occur, and there are various types of accident s. Accident reports record detailed information about different types of acciden ts in text form.” Our news journalists obtained a quote from the research from the Qingdao Univers ity of Technology, “However, effectively utilizing such unstructured data presen ts a significant challenge. Text mining ™provides a viable foundation for addre ssing this challenge, but related studies have limitations in risk feature extra ction and lack of in-depth analysis capability. To address the deficiencies of e xisting studies and provide a feasible strategy for identifying key risk factors in the metro construction domain, this paper proposes an integrated model combi ning TM and machine learning-based Bayesian networks. Firstly, the term frequenc y-inverse document frequency (TF-IDF) algorithm in TM was used to separately ext ract the direct and indirect cause factors from the accident reports, with the m issing factors supplemented using the TextRank algorithm. Then, depending on the assumption of whether to consider the conditional independence between factors, an improved naive Bayesian network (NBN) and a tree-augmented naive Bayesian ne twork (TAN) were built based on the extracted factors and the corresponding acci dent types, respectively, for further in-depth analysis. Finally, the training s et was divided to train the two network models, and sensitivity analysis was use d to identify the key risk factors. Using 162 accident reports from China as an application example, the results showed that TAN exhibited a higher average accu racy (79.62 %) in the test set compared with the improved NBN (71.75 %), and the importance of risk factors for different accident types was successfully ranked from multiple perspectives using TAN. Meanwhile, some n ew insights into metro accidents in China were obtained, which can support decis ion-making for accident prevention and control.”
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 originating from the Uni versity of Washington by NewsRx correspondents, research stated, “Motivated by r ecent experimental observations of opposite Chern numbers in R-type twisted MoTe 2 and WSe2 homobilayers, we perform large-scale density-functional-theory calcul ations with machine learning force fields to investigate moire band topology acr oss a range of twist angles in both materials.” The news correspondents obtained a quote from the research from University of Wa shington: “We find that the Chern numbers of the moire frontier bands change sig n as a function of twist angle, and this change is driven by the competition bet ween moire ferroelectricity and piezoelectricity. Our large-scale calculations, enabled by machine learning methods, reveal crucial insights into interactions a cross different scales in twisted bilayer systems.”
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 - Intelligent Systems are discussed in a new report. According to news reporting out of Heilongjiang, People’s Republic of China, by NewsRx editors, research st ated, “The accurate prediction of a lithium-ion battery’s State of Health is of critical importance for efficient battery health management. Existing data-drive n estimation methodologies grapple with issues such as high model complexity and a dearth of guidance from prior knowledge, which impose constraints on their ef ficacy.” Financial supporters for this research include Natural Science Foundation of Hei longjiang Province, Natural Science Foundation of Heilongjiang Province.
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