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 originating from Los Angeles, California, by News Rx correspondents, research stated, “In a mission with significant uncertainty d ue to intermittent communications, delayed information flow, and robotic failure s, the role of human supervisors is extremely challenging. As and when any new i nformation arrives, humans must infer both the existing and predicted future sta tes, identify potential contingencies, and update task assignments to robots rap idly.” Financial support for this research came from U.S. Army Combat Capabilities Deve lopment Command Army Research Laboratory (DEVCOM ARL).
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 originating from Brand enburg an der Havel, Germany, by NewsRx correspondents, research stated, “Artifi cial Intelligence (AI) is a dynamic area of computer science that is constantly expanding its practical benefits in various fields. The aim of this study was to analyze AI-guided radiological assessment of femoral neck fractures by performi ng a systematic review and multilevel meta-analysis of primary studies.” Our news editors obtained a quote from the research from University Hospital, “T he study protocol was registered in the International Prospective Register of Sy stematic Reviews (PROSPERO) on May 21, 2024 [CRD42024541055] . The updated Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were strictly followed. A systematic literature search of P ubMed, Web of Science, Ovid (Med), and Epistemonikos databases was conducted unt il May 31, 2024. Critical appraisal using the Quality Assessment of Diagnostic A ccuracy Studies-2 (QUADAS-2) tool showed that the overall quality of the include d studies was moderate. In addition, publication bias was presented in funnel pl ots. A frequentist multilevel meta-analysis was performed using a random effects model with inverse variance and restricted maximum likelihood heterogeneity est imator with Hartung-Knapp adjustment. The accuracy between AI-based and human as sessment of femoral neck fractures, sensitivity and specificity with 95 % confidence intervals (CIs) were calculated. Study heterogeneity was assessed usi ng the Higgins test I (low heterogeneity <25%, moderate heterogeneity: 25%-75%, and high heterogenei ty >75%). Finally, 11 studies with a total of 21,163 radiographs were included for meta-analysis. The results of the study quality assessment using the QUADAS-2 tool are presented in Table 2. The funnel plots indicated a moderate publication bias. The AI showed excellent accuracy in assessment of femoral neck fractures (Accuracy = 0.91, 95% CI 0.8 3 to 0.96; I = 99%; p<0.01). The AI showed go od sensitivity in assessment of femoral neck fractures (Sensitivity = 0.87, 95% CI 0.77 to 0.93; I = 98%; p<0.01). The AI sho wed excellent specificity in assessment of femoral neck fractures (Specificity = 0.91, 95% CI 0.77 to 0.97; I = 97%; p<0.01). AI-guided radiological assessment of femoral neck fractures showed excel lent accuracy and specificity as well as good sensitivity.”
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 Amsterdam, Neth erlands, by NewsRx correspondents, research stated, “The aim of this study was t o validate a previously developed deep learning model in 5 independent clinical trials. The predictive performance of this model was compared with the internati onal prognostic index (IPI) and 2 models incorporating radiomic PET/CT features (clinical PET and PET models).” Our news journalists obtained a quote from the research from Amsterdam Universit y Medical Center, “In total, 1,132 diffuse large B-cell lymphoma patients were i ncluded: 296 for training and 836 for external validation. The primary outcome w as 2-y time to progression. The deep learning model was trained on maximum-inten sity projections from PET/CT scans. The clinical PET model included metabolic tu mor volume, maximum distance from the bulkiest lesion to another lesion, SUV, ag e, and performance status. The PET model included metabolic tumor volume, maximu m distance from the bulkiest lesion to another lesion, and SUV Model performance was assessed using the area under the curve (AUC) and Kaplan-Meier curves. The IPI yielded an AUC of 0.60 on all external data. The deep learning model yielded a significantly higher AUC of 0.66 (<0.01). For each indi vidual clinical trial, the model was consistently better than IPI. Radiomic mode l AUCs remained higher for all clinical trials. The deep learning and clinical P ET models showed equivalent performance (AUC, 0.69; > 0. 05). The PET model yielded the highest AUC of all models (AUC, 0.71; <0.05). The deep learning model predicted outcome in all trials with a higher pe rformance than IPI and better survival curve separation.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics have been pr esented. According to news reporting out of Shenzhen, People’s Republic of China , by NewsRx editors, research stated, “Multirobot flocking possesses extraordina ry advantages over a single-robot system in diverse domains, but it is challengi ng to ensure safe and optimal performance in congested environments. Hence, this article is focused on the investigation of distributed optimal flocking control for multiple robots in crowded environments.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Guang Dong Basic and Applied Basic Research Foundation, Shen zhen Science and Technology Program.
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 Nanjing, People’s Repu blic of China, by NewsRx correspondents, research stated, “In this work, HCHO ox idation on metal single atom (from Sc to Zn) catalysts loaded on single carbon v acancy graphene (M-SG) was comprehensively studied through density functional th eory calculations. Results show that the lowest dissociation barrier (Ebar_ O2) for the O2 molecule is 0.91 eV on Cr-SG, which is expected to endow Cr-SG wi th the best performance towards HCHO oxidation.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC), Fundame ntal Research Funds for the Central Universities, High Performance Computing Pla tform, Hohai University.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in Nanotechnology - N anoindentation. According to news reporting from Denton, Texas, by NewsRx journa lists, research stated, “Microstructures of additively manufactured (AM) materia ls are highly heterogeneous, periodic, and hierarchical at various length scales , leading to complex mechanical response. In this study, nanoindentation trend a nalysis combined with machine learning (ML) was used to unravel the hierarchical and heterogeneous microstructures and associated multiscale mechanical response s in a laser-directed energy deposited low-alloy martensitic steel.” Funders for this research include Army Research Laboratory, USA, University of N orth Texas.
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 from Cartagena, Spain, by NewsRx journalists , research stated, “Robot vision, enabled by deep learning breakthroughs, is gai ning momentum in the industry 4.0 digitization process.” Our news editors obtained a quote from the research from Universidad Politecnica de Cartagena: “The present investigation describes a robotic grasp detection ap plication that makes use of a two-finger gripper and an RGB-D camera linked to a collaborative robot. The visual recognition system, which is integrated with ed ge computing units, conducts image recognition for faulty items and calculates t he position of the robot arm. Identifying deformities in object photos, training and testing the images with a modified version of the You Only Look Once (YOLO) method, and establishing defect borders are all part of the process. Signals ar e subsequently sent to the robotic manipulator to remove the faulty components.”
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 artificial intelligence. According to news reporting out of West Lafayette, Indi ana, by NewsRx editors, research stated, “This article examines issues of authen ticity involved in using generative AI to compose technical and professional com munication (TPC) documents.” Our news reporters obtained a quote from the research from Purdue University: “A uthenticity is defined through an Aristotelian understanding of ethos, which inc ludes goodwill ( eunoia), practical wisdom ( phronesis), virtuousness ( arete), and Fromm’s concepts of true self and pseudo self. The authors conducted an init ial analysis of AI affordances that align with TPC concerns-genre, plain languag e, and grammatical/mechanical correctness.”
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 Dublin, Irel and, by NewsRx correspondents, research stated, “Automated machine learning (Aut oML) solutions can bridge the gap between new computational advances and their r eal-world applications by enabling experimental scientists to build their own cu stom models. We examine different steps in the development life-cycle of peptide bioactivity binary predictors and identify key steps where automation cannot on ly result in a more accessible method, but also more robust and interpretable ev aluation leading to more trustworthy models.” Financial supporters for this research include Science Foundation Ireland, Europ ean Union’s Horizon 2020 research and innovation programme.
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 Porto Alegre, Brazil, by NewsRx jour nalists, research stated, “This study aims to employ machine learning, specifica lly artificial neural networks (ANNs), to predict the flow curve of hot-deformed steel alloys. The method involved creating a dense ANN with two hidden layers, trained with data from 70 steel classes, including information on chemical compo sition, temperature, and strain rate.” Funders for this research include Conselho Nacional de Desenvolvimento Cientific o e Tecnologico (CNPQ), Coordenacao de Aperfeicoamento de Pessoal de Nivel Super ior (CAPES). The news correspondents obtained a quote from the research from Federal Universi ty Rio Grande do Sul, “The results indicate robustness and good generalization c apability, with a mean absolute error of 11.4 MPa and a mean squared error of 10 .3 MPa. The model demonstrates an R2 value of 0.98, highlighting its effectivene ss in explaining variability in the data.”
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