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    New Robotics Study Findings Have Been Reported from Tokyo Institute of Technolog y (Simultaneous identification of dynamics parameters and spillover of multi-lin k system in periodic motion and control system design)

    29-29页
    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 reporting out of the Tokyo Institute of Technolog y by NewsRx editors, research stated, “Modeling methods of a robot dynamics incl ude (i) obtaining the equations of motion and identifying the dynamics parameter s, and (ii) system identification of the robot dynamical characteristics.” The news editors obtained a quote from the research from Tokyo Institute of Tech nology: “However, the parameters obtained in (i) are approximate solutions whose accuracy depends on the motion and environment in which the robot is operated, because the actual robot is finer and includes un-modeled dynamics. Therefore, a n appropriate evaluation index is required for identification. In (ii), the accu racy is low in the high-frequency domain due to the S/N ratio problem, which oft en causes spillover. In addition, in closed-loop identification, the inverse fun ction of the controller is identified due to noises. In this paper, we focus on the periodic motion of the end-effector of a planar 3-link manipulator and deriv e an error equation that exploits the periodicity of the motion to simultaneousl y identify the dynamics parameters and spillover. In particular, by selecting th e identification object to realize an open-loop identification, the identificati on of spillover has high accuracy.”
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    New Machine Learning Study Findings Recently Were Reported by Researchers at Fri edrich-Alexander-University Erlangen-Nurnberg (FAU) (Leveraging Interpretable Ma chine Learning In Intensive Care)

    30-30页
    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 reporting from Nurnberg, Germany, by NewsRx j ournalists, research stated, “In healthcare, especially within intensive care un its (ICU), informed decision-making by medical professionals is crucial due to t he complexity of medical data. Healthcare analytics seeks to support these decis ions by generating accurate predictions through advanced machine learning (ML) m odels, such as boosted decision trees and random forests.” Financial supporters for this research include Projekt DEAL, Federal Ministry of Education & Research (BMBF), Nvidia Corporation.
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    Researcher from University of Salford Reports Recent Findings in Robotics (A Sta tistical Analysis of Commercial Articulated Industrial Robots and Cobots)

    31-32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 have been published. According to news reporting from Manchester, United Kingdom, by NewsRx journalists, research stated, “This paper aims to elucidate the state-of -the-art, prevailing priorities, and the focus of the industry, and identify bot h limitations and potential gaps regarding industrial robots and collaborative r obots (cobots). Additionally, it outlines the advantages and disadvantages of co bots compared to traditional industrial robots.” Funders for this research include Research England Development.
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    Findings from School of Mechanical Engineering in Robotics Reported (Behaviour-d efined Navigation Framework for Dynamical Obstacle Avoidance In Multi-robot Syst ems Consisting of Holonomic Robots)

    32-32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 Robotics is the subjec t of a report. According to news reporting out of Vellore, India, by NewsRx edit ors, research stated, “Dynamical obstacle avoidance is a challenging problem in the field of autonomous robot navigation. Current research in this field has bee n mostly limited to single robots, thus, there exists a gap in research in the f ield of dynamical obstacle avoidance in multi robot systems.” Our news journalists obtained a quote from the research from the School of Mecha nical Engineering, “While rich literature is available on multirobot systems, th is paper attempts to propose a novel navigation framework for an environment whi ch includes multiple robots. The proposed navigation framework applies certain b ehaviours to ensure a safe trajectory for the multi-robot systems. As opposed to other reported literature which focused on implementing their algorithms on non -holonomic robots, the proposed navigation framework is implemented on several h olonomic robots. Simulations and real-life experiments were carried out using th e proposed framework. Dynamic obstacles are considered in the environment and Kh ep era IV robots are used to conduct real-life experiments. Two dynamic obstacle s were placed at different positions in the workspace. These obstacles had linea r movements, whereby each robot could move horizontally and vertically across th e workspace. Three experimental trials were performed.”
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    Report Summarizes Robotics and Automation Study Findings from Chinese Academy of Sciences (Intensity Triangle Descriptor Constructed From High-resolution Spinni ng Lidar Intensity Image for Loop Closure Detection)

    33-33页
    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 - Robotics and Automation. According to news reporting originating in Bei jing, People’s Republic of China, by NewsRx journalists, research stated, “LiDAR -based loop closure detection is a crucial part of realizing robust SLAM algorit hms for intelligent vehicles with LiDAR sensors. Existing methods often reduce t he keypoint dimension to encode the global descriptor, which sacrifices the free dom of loop detection and correction.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
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    Department of Urology Reports Findings in Prostatectomy (Elevating precision: A thorough investigation of multiparametric prostate MRI for prolonged insights in to early continence prediction after robot-assisted laparoscopic prostatectomy)

    34-34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 Surgery - Prostatectom y is the subject of a report. According to news reporting originating in Istanbu l, Turkey, by NewsRx journalists, research stated, “While radical prostatectomy stands out as one of the most effective curative treatments for prostate cancer, it does come with annoying side effects, such as urinary incontinence (UI). We aimed to investigate the predictability of UI using MRI measurements, along with clinical and disease-related variables.” The news reporters obtained a quote from the research from the Department of Uro logy, “We included 191 patients who underwent robot-assisted laparoscopic radica l prostatectomy between July 2020 and October 2022 in the study. Preoperative MR Is of the patients are re-evaluated by an experienced uroradiologist, and membra nous urethral length (MUL), urethra wall thickness, levator ani thickness, outer levator distance, Lee’s apex shape, intravesical prostate protrusion length, pr ostate apex depth, and pubic height measurements were made. Additionally, retros pective data on patients’ age, BMI, PSA, PSA density, prostate volume, IPSS, cli nical stage, and nerve-sparing status were collected. Patients were categorized into two groups based on continence status in the third postoperative month: con tinent or incontinent. The definition of UI was accepted as the use of one or mo re pads per day. UI was observed in 38.21 % of the patients in the postoperative third month. Among MRI measurements, only MUL showed a significan t relationship with UI (p <0.001). IPSS (p = 0.004) and Cl inical Stage (p <0.001) were also significantly associated with continence status. Logistic regression analysis identified BMI (p = 0.023; CI 0.73-0.97), IPSS (p = 0.002; CI 1.03-1.17), MUL (p = 0.001; CI 0.66-0.90), a nd Clinical Stage (p <0.001; CI 1.53-2.71) as significant predictors. In Multivariable Regression analysis, Clinical Stage emerged as the most powerful predictor of UI (p <0.001). Except for MUL, MRI measurements may not predict postoperative UI. A combination of IPSS, clinic al stage, and MUL effectively informs patients about postoperative outcomes.”
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    First Affiliated Hospital of Xinjiang Medical University Reports Findings in Str oke (Machine learning approaches to identify the link between heavy metal exposu re and ischemic stroke using the US NHANES data from 2003 to 2018)

    35-36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 Cerebrovascular Diseas es and Conditions - Stroke is the subject of a report. According to news reporti ng originating in Xinjiang, People’s Republic of China, by NewsRx journalists, r esearch stated, “There is limited understanding of the link between exposure to heavy metals and ischemic stroke (IS). This research aimed to develop efficient and interpretable machine learning (ML) models to associate the relationship bet ween exposure to heavy metals and IS.” The news reporters obtained a quote from the research from the First Affiliated Hospital of Xinjiang Medical University, “The data of this research were obtaine d from the National Health and Nutrition Examination Survey (US NHANES, 2003-201 8) database. Seven ML models were used to identify IS caused by exposure to heav y metals. To assess the strength of the models, we employed 10-fold crossvalida tion, the area under the curve (AUC), F1 scores, Brier scores, Matthews correlat ion coefficient (MCC), precision-recall (PR) curves, and decision curve analysis (DCA) curves. Following these tests, the best-performing model was selected. Fi nally, the DALEX package was used for feature explanation and decision-making vi sualization. A total of 15,575 participants were involved in this study. The bes t-performing ML models, which included logistic regression (LR) (AUC: 0.796) and XGBoost (AUC: 0.789), were selected. The DALEX package revealed that age, total mercury in blood, poverty-to-income ratio (PIR), and cadmium were the most sign ificant contributors to IS in the logistic regression and XGBoost models.”
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    Recent Research from HeNan Polytechnic University Highlight Findings in Machine Learning (Density Functional Theory and Machine Learning of Transition Metals In Mo2c for Gas Sensors)

    35-35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 from Jiaozuo, People’s Repu blic of China, by NewsRx journalists, research stated, “Gas accumulation is the primary cause of explosions in underground mines, and preventing it requires eff ective gas detection. To address this, we propose an approach combining machine learning (ML) and density functional theory (DFT) for designing nanoscale gas se nsors.” Financial support for this research came from Key Projects of NSFC-Henan Joint F und.
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    National University of Sciences Researcher Describes Recent Advances in Optical Character Recognition (Comparative Approach to De-Noising TEMPEST Video Frames)

    36-37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 optical character recognition. According to news reporting out of Bucharest, Rom ania, by NewsRx editors, research stated, “Analysis of unintended compromising e missions from Video Display Units (VDUs) is an important topic in research commu nities.”Funders for this research include National University of Science And Technology Politehnica Bucharest’s Pubart Project.
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    Study Results from Massachusetts Institute of Technology Update Understanding of Robotics (Learning-based Bayesian Inference for Testing of Autonomous Systems)

    37-38页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Robotics have been publi shed. According to news originating from Cambridge, Massachusetts, by NewsRx cor respondents, research stated, “For the safe operation of robotic systems, it is important to accurately understand its failure modes using prior testing. Hardwa re testing of robotic infrastructure is known to be slow and costly.” Funders for this research include National Aeronautics and Space Administration (NASA) ULI, Air Force Office of Scientific Research (AFOSR).
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