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    Findings on Robotics Reported by Investigators at Zhejiang Science Technical University (Finite-time Robust Formation Control of Multiple Aerial Robotic Vehicles With Uncertainties and Time-varying Complex Perturbations)

    28-28页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting originating in Hangzhou, People's Republic of China, by NewsRx journalists, research stated, “Formation control of aerial robotic vehicles (ARVs) has a wide range of applications in the battlefield reconnaissance, medical rescue and load transportation, etc. System parameter variations and complex disturbances are inevitable in the formation control of ARVs, and the effects of them on the formation stability control of ARVs are unnegligible.” Financial supporters for this research include Zhejiang Sci-Tech University, National Natural Science Foundation of China (NSFC), Natural Science Foundation of Zhejiang Province. The news reporters obtained a quote from the research from Zhejiang Science Technical University, “This paper addresses the robust formation control problem of finite-time leader-follower for multiple ARVs suffering from parameter uncertainties and time-varying perturbations. To ensure the states (e.g. position and velocity) of all followers to converge to leader in finite time, a novel finite-time high-order sliding mode consensus control (HOSMCC) scheme is designed. To better cope with the parameter uncertainties and time-varying disturbances, improve formation control accuracy and achieve the robust formation control of finite-time leader-follower in multiple ARV systems, a new finite time high-order sliding mode formation control (HOSMFC) scheme on the basis of finite-time HOSMCC is proposed. The finite-time stability of multi-ARV formation control system is guaranteed, and the desired formation pattern of multi-ARV systems is achieved using Lyapunov stability theorem. Performance comparisons with proportional differential formation controller (PDFC) and sliding mode formation controller (SMFC) are studied on a four-ARV formation control system.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    University of Cambridge Reports Findings in Machine Learning (Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity)

    29-29页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of Cambridge, United Kingdom, by NewsRx editors, research stated, “In the early stages of drug development, large chemical libraries are typically screened to identify compounds of promising potency against the chosen targets. Often, however, the resulting hit compounds tend to have poor drug metabolism and pharmacokinetics (DMPK), with negative developability features that may be difficult to eliminate.” Our news journalists obtained a quote from the research from the University of Cambridge, “Therefore, starting the drug discovery process with a ‘null library', compounds that have highly desirable DMPK properties but no potency against the chosen targets, could be advantageous. Here, we explore the opportunities offered by machine learning to realize this strategy in the case of the inhibition of a-synuclein aggregation, a process associated with Parkinson's disease. We apply MolDQN, a generative machine learning method, to build an inhibitory activity against a-synuclein aggregation into an initial inactive compound with good DMPK properties.”
      原文链接:
    • NETL
    • NSTL

    Researchers from National Scientific and Technical Research Council (CONICET) Detail Research in Machine Learning (Quantifying the contribution of environmental variables to cyclists' exposure to PM2.5 using machine learning techniques)

    30-30页
    查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting from the National Scientific and Technical Research Council (CONICET) by NewsRx journalists, research stated, “Cyclists are particularly vulnerable to travel-related exposure to air pollution. Under- standing the factors that increase exposure is crucial for promoting healthier urban environments.” Funders for this research include Agencia Nacional De Promocion Cientifica Y Tecnologica; Fondo Para La Investigacion Cientifica Y Tecnologica. The news correspondents obtained a quote from the research from National Scientific and Technical Research Council (CONICET): “Machine learning models have successfully predicted air pollutant concentrations, but they tend to be less interpretable than classical statistical ones, such as linear models. This study aimed to develop a predictive model to assess cyclists' exposure to fine particulate matter (PM2.5) in urban environments. The model was generated using geo-temporally referenced data and machine learning techniques. We explored several models and found that the gradient boosting machine learning model best fitted the PM2.5 predictions, with a minimum root mean square error value of 5.62 mg m-3. The variables with greatest influence on cyclist exposure were the temporal ones (month, day of the week, and time of the day), followed by meteorological variables, such as temperature, relative humidity, wind speed, wind direction, and atmospheric pressure. Additionally, we considered relevant attributes, which are partially linked to spatial characteristics. These attributes encompass street typology, vegetation density, and the flow of vehicles on a particular street, which quantifies the number of vehicles passing a given point per minute. Mean PM2.5 concentration was lower in bicycle paths away from vehicular traffic than in bike lanes along streets.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Department of Urology Reports Findings in Prostatectomy (Does Retzius-Sparing robot-assisted radical prostatectomy guarantee optimal urinary continence recovery across all ages?)

    31-32页
    查看更多>>摘要：New research on Surgery - Prostatectomy is the subject of a report. According to news reporting out of Milan, Italy, by NewsRx editors, research stated, “The association between age at surgery and urinary continence (UC) recovery after Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) is not well established. We addressed this knowledge gap, relying on a large series of 1,417 patients treated with RS-RARP at a high-volume centre between 2010 and 2021.” Our news journalists obtained a quote from the research from the Department of Urology, “Multivariable logistic models, as well as LOESS plot functions were performed. The probability of immediate, as well as 12-month UC-recovery progressively declined with increasing age at surgery, and per 5-years age at surgery increase reached the independent predictor status for both immediate and 12-month UC-recovery.” According to the news editors, the research concluded: “These findings may significantly improve the quality of patient counseling regarding RS-RARP.” This research has been peer-reviewed.
      原文链接:
    • NETL
    • NSTL

    Data from Wuxi Institute of Technology Update Knowledge in Robotics (Image Recognition Technology Applied to the Design of Mobile Platform for Warehouse Logistics Robots)

    31-31页
    查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news originating from Jiangsu, People's Republic of China, by NewsRx correspondents, research stated, “This paper first studies the processing flow of image processing technology that preprocesses the image and adopts the method of polygonal approximation to identify the shape and localize the moving target.” The news correspondents obtained a quote from the research from Wuxi Institute of Technology: “Then, the mobile platform of the warehouse logistics robot is designed. Then, the vision system of the robot was designed using image recognition technology to realize obstacle collision prediction and route planning. Finally, the robot's localization and grasping abilities, trajectory following performance, and semantic segmentation abilities are analyzed using comparative experiments. The successful localization and grasping rates of the warehouse robots are all higher than 93%, and the trajectory following the straight line road section is better, with a maximum error of less than 21 mm.”
      原文链接:
    • NETL
    • NSTL

    Investigators at Xi'an Jiaotong University Describe Findings in Robotics (Semg-based End-to-end Continues Prediction of Human Knee Joint Angles Using the Tightly Coupled Convolutional Transformer Model)

    32-33页
    查看更多>>摘要：2024 FEB 05 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics are presented in a new report. According to news originating from Xi'an, People's Republic of China, by NewsRx correspondents, research stated, “Wearable exoskeleton robots can promote the rehabilitation of patients with physical dysfunction. And improving human-computer interaction performance is a significant challenge for exoskeleton robots.” Funders for this research include National Key Research and Development Program, Shaanxi Province Key Research and Development Program. Our news journalists obtained a quote from the research from Xi'an Jiaotong University, “The traditional feature extraction process based on surface Electromyography(sEMG) is complex and requires manual intervention, making real-time performance difficult to guarantee. In this study, we propose an end-to-end method to predict human knee joint angles based on sEMG signals using a tightly coupled convolutional transformer (TCCT) model. We first collected sEMG signals from 5 healthy subjects. Then, the envelope was extracted from the noise-removed sEMG signal and used as the input to the model. Finally, we developed the TCCT model to predict the knee joint angle after 100 ms. For the prediction performance, we used the Root Mean Square Error(RMSE), Pearson Correlation Coefficient(CC), and Adjustment R-2 as metrics to evaluate the error between the actual knee angle and the predicted knee angle. The results show that the model can predict the human knee angle quickly and accurately. The mean RMSE, Adjustment R-2, and (CC) values of the model are 3.79(degrees), 0.96, and 0.98, respectively, which are better than traditional deep learning models such as Informer (4.14, 0.95, 0.98), CNN (5.56, 0.89, 0.96) and CNN- BiLSTM (3.97, 0.95, 0.98). In addition, the prediction time of our proposed model is only 11.67 +/-0.67 ms, which is less than 100 ms.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Stockholm University Reports Findings in Machine Learning (Closing the Organofluorine Mass Balance in Marine Mammals Using Suspect Screening and Machine Learning-Based Quantification)

    33-34页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news originating from Stockholm, Sweden, by NewsRx correspondents, research stated, “High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening has identified a growing number of novel per- and polyfluoroalkyl substances (PFASs) in the environment. However, without analytical standards, the fraction of overall PFAS exposure accounted for by these suspects remains ambiguous.” Our news journalists obtained a quote from the research from Stockholm University, “Fortunately, recent developments in ionization efficiency () prediction using machine learning offer the possibility to quantify suspects lacking analytical standards. In the present work, a gradient boosted tree-based model for predicting log in negative mode was trained and then validated using 33 PFAS standards. The root- mean-square errors were 0.79 (for the entire test set) and 0.29 (for the 7 PFASs in the test set) log units.” According to the news editors, the research concluded: “Thereafter, the model was applied to samples of liver from pilot whales (n = 5; East Greenland) and white beaked dolphins (n = 5, West Greenland; n = 3, Sweden) which contained a significant fraction (up to 70%) of unidentified organofluorine and 35 unquantified suspect PFASs (confidence level 2-4). -based quantification reduced the fraction of unidentified extractable organofluorine to 0-27%, demonstrating the utility of the method for closing the fluorine mass balance in the absence of analytical standards.”
      原文链接:
    • NETL
    • NSTL

    Copenhagen Academy for Medical Education and Simulation (CAMES) Reports Findings in Robotics (Surgical gestures can be used to assess surgical competence in robot-assisted surgery : A validity investigating study of simulated RARP)

    34-35页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news originating from Copenhagen, Denmark, by NewsRx correspondents, research stated, “To collect validity evidence for the assessment of surgical competence through the classification of general surgical gestures for a simulated robot-assisted radical prostatectomy (RARP). We used 165 video recordings of novice and experienced RARP surgeons performing three parts of the RARP procedure on the RobotiX Mentor.” Financial support for this research came from Copenhagen University. Our news journalists obtained a quote from the research from Copenhagen Academy for Medical Education and Simulation (CAMES), “We annotated the surgical tasks with different surgical gestures: dissection, hemostatic control, application of clips, needle handling, and suturing. The gestures were analyzed using idle time (periods with minimal instrument movements) and active time (whenever a surgical gesture was annotated). The distribution of surgical gestures was described using a one-dimensional heat map, snail tracks. All surgeons had a similar percentage of idle time but novices had longer phases of idle time (mean time: 21 vs. 15 s, p＜0.001). Novices used a higher total number of surgical gestures (number of phases: 45 vs. 35, p＜0.001) and each phase was longer compared with those of the experienced surgeons (mean time: 10 vs. 8 s, p＜0.001). There was a different pattern of gestures between novices and experienced surgeons as seen by a different distribution of the phases. General surgical gestures can be used to assess surgical competence in simulated RARP and can be displayed as a visual tool to show how performance is improving. The established pass/fail level may be used to ensure the competence of the residents before proceeding with supervised real-life surgery.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Researcher from Universidad Politecnica de Madrid Reports on Findings in Robotics (Design, Manufacturing, and Open-Loop Control of a Soft Pneumatic Arm)

    35-36页
    查看更多>>摘要：Investigators discuss new findings in robotics. According to news reporting originating from Madrid, Spain, by NewsRx correspondents, research stated, “Soft robots distinguish themselves from traditional robots by embracing flexible kinematics.” The news editors obtained a quote from the research from Universidad Politecnica de Madrid: “Because of their recent emergence, there exist numerous uncharted territories, including novel actuators, manufacturing processes, and advanced control methods. This research is centred on the design, fabrication, and control of a pneumatic soft robot. The principal objective is to develop a modular soft robot featuring multiple segments, each one with three degrees of freedom. This yields a tubular structure with five independent degrees of freedom, enabling motion across three spatial dimensions. Physical construction leverages tin-cured silicone and a wax-casting method, refined through an iterative processes. PLA moulds that are 3D-printed and filled with silicone yield the desired model, while bladder-like structures are formed within using solidified paraffin wax-positive moulds.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Investigators from Changchun University of Technology Zero in on Intelligent Systems (Load Balancing of Multi-agv Road Network Based On Improved Q-learning Algorithm and Macroscopic Fundamental Diagram)

    36-37页
    查看更多>>摘要：Investigators publish new report on Machine Learning - Intelligent Systems. According to news reporting originating from Changchun, People's Republic of China, by NewsRx correspondents, research stated, “To address the challenges of traffic congestion and suboptimal operational efficiency in the context of large-scale applications like production plants and warehouses that utilize multiple automatic guided vehicles (multi-AGVs), this article proposed using an Improved Q-learning (IQL) algorithm and Macroscopic Fundamental Diagram (MFD) for the purposes of load balancing and congestion discrimination on road networks. Traditional Q-learning converges slowly, which is why we have proposed the use of an updated Q value of the previous iteration step as the maximum Q value of the next state to reduce the number of Q value comparisons and improve the algorithm's convergence speed.” Financial support for this research came from Jilin Province Major Science and Technology Special Project “Research on Repeat Positioning Accuracy Technology of AGV.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature