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    Reports Summarize Machine Learning Study Results from National University of Sin gapore [Machine Learning-guided Design and Synthesis of Eco-f riendly Poly(Ethylene Oxide) Membranes for Highefficacy Co2/n2 Separation]

    57-58页
    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 in Singapore, Sin gapore, by NewsRx journalists, research stated, "Machine learning (ML)-guided po lymer design and synthesis will enable the next-generation membrane material dis covery for CO2 capture. Herein, ML is leveraged to establish a structure-perform ance relationship for the eco-friendly poly(ethylene oxide) (PEO) membrane and g uide its design for high-efficacy CO2/N-2 separation." Financial supporters for this research include National Key Research & Development Program of China, Agency for Science Technology & Rese arch (A*STAR), Chevron Singapore Pte Ltd..

    New Findings from University of Batna in the Area of Machine Learning Reported ( Byzantine Fault Tolerance In Distributed Machine Learning: a Survey)

    58-59页
    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 Batna, Alg eria, by NewsRx correspondents, research stated, "Byzantine Fault Tolerance (BFT ) is crucial for ensuring the resilience of Distributed Machine Learning (DML) s ystems during training under adversarial conditions. Among the rising corpus of research on BFT in DML, there is no comprehensive classification of techniques o r broad analysis of different approaches." Our news editors obtained a quote from the research from the University of Batna,"This paper provides an in-depth survey of recent advancements in BFT for DML, with a focus on first-order optimisation methods, particularly, the popular one Stochastic Gradient Descent (SGD) during the training phase. We offer a novel c lassification of BFT approaches based on characteristics such as the communicati on process, optimisation method, and topology setting. This classification aims to enhance the understanding of various BFT methods and guide future research in addressing open challenges in the field."

    Reports Summarize Robotics and Automation Study Results from Tongji University ( Log-lio2: a Lidar-inertial Odometry With Efficient Uncertainty Analysis)

    59-60页
    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 Robotics-Ro botics and Automation have been published. According to news originating from Sh anghai, People's Republic of China, by NewsRx correspondents, research stated, " Uncertainty in LiDAR measurements, stemming from factors such as range sensing, is crucial for LIO (LiDAR-Inertial Odometry) systems as it affects the accurate weighting in the loss function. While recent LIO systems address uncertainty rel ated to range sensing, the impact of incident angle on uncertainty is often over looked by the community." Financial support for this research came from National Key Research & Development Program of China. Our news journalists obtained a quote from the research from Tongji University, "Moreover, the existing uncertainty propagation methods suffer from computationa l inefficiency. This letter proposes a comprehensive point uncertainty model that accounts for both the uncertainties from LiDAR measurements and surface charac teristics, along with an efficient local uncertainty analytical method for LiDAR -based state estimation problem. We employ a projection operator that separates the uncertainty into the ray direction and its orthogonal plane. Then, we derive incremental Jacobian matrices of eigenvalues and eigenvectors w.r.t. points, wh ich enables a fast approximation of uncertainty propagation. This approach elimi nates the requirement for redundant traversal of points, significantly reducing the time complexity of uncertainty propagation from O (n) O(1) when a new point is added."

    Study Findings from Georgia Institute of Technology Provide New Insights into Ar tificial Intelligence (Applications of Artificial Intelligence/machine Learning To High-performance Composites)

    60-61页
    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 originating from Atlanta, Georgia, by NewsRx correspondents, research stated, "With the booming prosperity of artific ial intelligence (AI) technology, it triggers a paradigm shift in engineering fi elds including material science. The integration of AI and machine learning (ML) techniques in material science brings significant advancements in understanding and characterizing underlying physics." Funders for this research include National Science Foundation (NSF), National Sc ience Foundation (NSF). Our news journalists obtained a quote from the research from the Georgia Institu te of Technology, "Due to the overall outstanding properties compared to convent ional metallic materials, high-performance fiber reinforced polymer (FRP) compos ites have attracted great interest. This article aims to provide a comprehensive review of the stateof-the-art works of applying AI/ML methods in high-performan ce FRP composites, focusing on four critical stages throughout the product life cycle, i.e., design, manufacturing, testing, and monitoring. This present study covers the tasks of material development and selection, process modeling and opt imization, material property prediction, and damage diagnosis and prognosis in t he four stages, which are conducted with the aid of advanced AI/ ML algorithms."

    Findings on Machine Learning Reported by Investigators at Ho Chi Minh City Unive rsity of Technology (Stability Design Charts and Equations for Rectangular Tunne ls Using Terzaghi's Modified Stability Factors and Machine Learning)

    61-62页
    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 originating from Ho Chi Minh City, Vietnam, by New sRx correspondents, research stated, "The objective of this study is to investig ate the stability of plane strain rectangular tunnels under the effects of soil cohesion, surcharge loading, and soil unit weight. The novelty of the study is t o extend Terzaghi's bearing capacity equation approach for determining three tun nel stability factors (Nc, Ns, and N gamma) that can be used to evaluate a tunne l's stability." Financial supporters for this research include Ho Chi Minh City University of Te chnology (HCMUT), VNU-HCM.

    Research from School of Education Provides New Data on Artificial Intelligence ( Perceptions of students on artificial intelligencegenerated content avatar util ization in learning management system)

    62-62页
    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 Penang, Malaysia, by NewsRx editors, research stated, "Purpose-This study aims to explore students ' perceptions of the use of an artificial intelligence-generated content avatar (AIGC avatar) within a learning management system (LMS). Design/methodology/appr oach-This qualitative research involved seven postgraduate students." The news journalists obtained a quote from the research from School of Education : "Data were collected through individual, in-depth interviews. The videos of th e AIGC avatar, created using Leonardo, ChatGPT and Heygen, were uploaded to the LMS to communicate with students for the purposes of a welcome note, assignment guide, assignment feedback, tutorial reminders and preparation as well as to pro vide encouragement and study tips. Students were interviewed at the end of the s emester. Findings-The findings of this study indicated that the majority of pa rticipating students held positive perceptions regarding the use of the AIGC ava tar in the LMS. They reported that it enhanced their perceived instructor's soci al presence and motivation to learn. The assignment guide and feedback were part icularly valued by the participants. While some students noted the AIGC avatar's lack of naturalness, others appreciated the clear and professional speech it de livered. Research limitations/implications-The study was confined to seven stu dents from a single course at one institution, which may limit the generalizabil ity of the findings. Future research could involve a larger and more diverse gro up of participants."

    Findings from Northwest A&F University Yields New Findings on Agric ultural Robots (Fruit Flexible Collecting Trajectory Planning Based On Manual Sk ill Imitation for Grape Harvesting Robot)

    63-63页
    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 Agriculture-Agricultural Robots have been published. According to news reporting originatin g from Shaanxi, People's Republic of China, by NewsRx correspondents, research s tated, "The flexible collection is vital for the intelligent grape-picking robot . In view of the reliable operation method obtained by long-term training of hum an prior skill, a fruit flexible collecting trajectory planning method based on manual skill imitation for grape harvesting robot is proposed." Funders for this research include Beijing Municipal Science & Tech nology Commission, BAAFS Youth Research Foundation. Our news editors obtained a quote from the research from Northwest A& F University, "The method involves capturing manual teaching trajectory data usi ng a motion capture system, preprocessing the data, extracting features from mul tiple teaching trajectories, and forming a probability distribution through Gaus sian mixture model-Gaussian mixture regression (GMM-GMR). And combined with th e key point of manual operation trajectory, the general trajectory generated by GMR is segmented and further imitated by kernelized movement primitives (KMP) to obtain the reference trajectory, respectively. An optimization method for hyper parameter adaptation KMP (O-KMP) was proposed to meet the trajectory fitting eff ect of multiple key points. Mean square error (MSE) was used to evaluate the dev iation of the trajectory from the reference trajectory. The partial optimal traj ectory is selected and integrated into a single trajectory. Two experiments were conducted to investigate imitation: For the same starting and ending points tas k, the MSE of the trajectory generated by O-KMP decreased by 15.274% compared to the original fixed hyperparameter KMP. For different placement tasks,the MSE of the trajectory generated by the O-KMP decreased by 7.296% compared to the original KMP."

    Recent Studies from North China Institute of Aerospace Engineering Add New Data to Machine Learning (Monitoring water quality parameters of freshwater aquacultu re ponds using UAV-based multispectral images)

    64-64页
    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 artificial intelligence is now available. According to news originating from Hebei, People's Republic o f China, by NewsRx correspondents, research stated, "Monitoring water quality is crucial for water exchange, precise feeding, and quality control of water produ cts in freshwater aquaculture. In light of the issue of spatial heterogeneity in freshwater aquaculture pond waters and the constraints of conventional sensor d etection techniques and traditional machine learning models." The news editors obtained a quote from the research from North China Institute o f Aerospace Engineering: "In this study, UAV multispectral images were combined with four machine learning algorithms (Ridge, XGBoost, CatBoost, RF) and the Sta cking model to model the estimation of Chlorophyll a (Chla) and Turbidity and m ap their spatial distribution. The findings indicate that, in contrast to machin e learning models, the Stacking model of water quality parameter performs better with higher accuracy. Meanwhile,for Chl-a and Turbidity the optimal sub-model c ombination in the Stacking model varies, with the most effective estimation mode l for Chl-a concentration identified as RF-XGB-Ridge (R2 = 0.84, RMSE=1.882 g/L, MAE=3.433 g/L and Slope = 0.791). As to Turbidity, the RF-CAB-Ridge model demon strates superior performance, with macro-averaged precision (macro-p) of 93.3 %,macro-averaged recall (macro-R) of 88.8 %, macro-averaged F1-scor e (macro-F1) of 0.895, and Kappa coefficient of 0.813. Furthermore, the results of the joint analyses, which included measured samples and management measures a t the test site, demonstrated that the spatial distribution maps of Chl-a and Tu rbidity were in alignment with the current status of water quality at the test s ite. This consistency was observed across both temporal and spatial scales."

    Reports Summarize Artificial Intelligence Findings from Johns Hopkins University (Ai and Biosecurity: the Need for Governance)

    65-65页
    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 Artific ial Intelligence. According to news reporting from Baltimore, Maryland, by NewsR x journalists, research stated, "Governments should evaluate advanced models and if needed impose safety measures Great benefits to humanity will likely ensue f rom advances in artificial intelligence (AI) models trained on or capable of mea ningfully manipulating substantial quantities of biological data, from speeding up drug and vaccine design to improving crop yields (1-3). But as with any power ful new technology, such biological models will also pose considerable risks." Financial supporters for this research include Open Philanthropy, Effective Givi ng, Horizon Institute for Public Service, NIH National Center for Advancing Tran slational Sciences (NCATS). The news correspondents obtained a quote from the research from Johns Hopkins Un iversity, "Because of their general-purpose nature, the same biological model ab le to design a benign viral vector to deliver gene therapy could be used to desi gn a more pathogenic virus capable of evading vaccine-induced immunity (4). Volu ntary commitments among developers to evaluate biological models' potential dang erous capabilities are meaningful and important but cannot stand alone."

    Recent Findings in Robotics Described by Researchers from Dalian University of T echnology (Multimodal Conversion of a Magnetic Navigated Dual-hemisphere Capsule Robot Based On Self-standing Characteristics)

    66-66页
    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 reporting originating from Dalian, Peop le's Republic of China, by NewsRx correspondents, research stated, "Capsules app lied in large-volume and unstructured organs, such as stomach and colon, should perform multimodal motion to effectively accomplish gastrointestinal tract diagn osis. For this purpose, a magnetic navigated dual-hemisphere capsule robot (DHCR ) actuated by the spatial universal rotating magnetic field (SURMF) is proposed, utilizing its passive and active modes for fixed-point posture adjustment and r olling locomotion, respectively." 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 the Dalian University o f Technology, "The DHCR exhibits a distinctive physical property-self-standing c haracteristics, which can specify vertically upward orientation as the starting posture and benchmark for multimodal motion after the DHCR undergoes complex mul timodal (pseudo-active, active, and passive modes) conversion. On the basis of t he momentum moment theorem, a general dynamic model is devised to reveal the mec hanism of multimodal transition through stability and posture response. Results show that the DHCR can flip spontaneously after applying SURMF and is finally in a stable passive mode with the vertically upward DHCR axis."