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    Capital Medical University Reports Findings in HIV/AIDS (Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study)

    48-49页
    查看更多>>摘要：New research on Immune System Diseases and Conditions - HIV/AIDS is the subject of a report. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “The study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources. Regression models were established based on RF, KNN, SVM, and XGB to predict the length of hospital stay using RMSE, MAE, MAPE, and , while classification models were established based on RF, KNN, SVM, NN, and XGB to predict risk of prolonged hospital stay using accuracy, PPV, NPV, specificity, sensitivity, and kappa, and visualization evaluation based on AUROC, AUPRC, calibration curves and decision curves of all models were used for internally validation.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa

    Recent Studies from Islamic Azad University Add New Data to Machine Learning (Stacking Ensemble-Based Machine Learning Model for Predicting Deterioration Components of Steel W-Section Beams)

    49-50页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting originating from Zanjan, Iran, by NewsRx correspondents, research stated, “The collapse evaluation of the structural systems under seismic loading necessitates identifying and quantifying deterioration components (DCs).” Our news journalists obtained a quote from the research from Islamic Azad University: “In the case of steel w-section beams (SWSB), three distinct types of DCs have been derived. These deterioration components for steel beams comprise the following: pre-capping plastic rotation (thp), post-capping plastic rotation (thpc), and cumulative rotation capacity (L). The primary objective of this research is to employ a machine learning (ML) model for accurate determination of these deterioration components. The stacking model is a powerful combination of meta-learners, which is used for better learning and performance of base learners. The base learners consist of AdaBoost, Random Forest (RF), and XGBoost. Among various machine learning algorithms, the stacking model exhibited superior functioning.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Data on Stroke Reported by Birgul Elmas Bodur and Colleagues (Effects of robotic-assisted gait training on physical capacity, and quality of life among chronic stroke patients: A randomized controlled study)

    50-51页
    查看更多>>摘要：New research on Cerebrovascular Diseases and Conditions - Stroke is the subject of a report. According to news reporting from Istanbul, Turkey, by NewsRx journalists, research stated, “Even though robotic therapy is becoming more commonly used in research protocols for lower limb stroke rehabilitation, there still is a significant gap between research evidence and its use in clinical practice. Therefore, the present study was designed assuming that the wearable mobile gait device training for chronic stroke patients might have different effects on functional independence when compared to training with a stationary gait device.”
      原文链接:
    • NETL
    • NSTL

    Research on Robotics Detailed by a Researcher at China University of Geosciences (Audio-Visual Bimodal Combination-Based Speaker Tracking Method for Mobile Robot)

    51-52页
    查看更多>>摘要：A new study on robotics is now available. According to news originating from Hubei, People’s Republic of China, by NewsRx editors, the research stated, “Initiative service is a key research direction for the new generation of service robots. It is important to automatically track humans for initiative service in human-robot interaction.” Funders for this research include College Students’ Innovative Entrepreneurial Training Plan Program; China University of Geosciences. Our news journalists obtained a quote from the research from China University of Geosciences: “To solve the problems of low precision and poor anti-interference capability of only using single-modal (audio or visual) information, a speaker positioning and tracking method based on an audio-visual bimodal combination is proposed. First, the azimuth of the speaker is obtained based on the time difference of arrival using a microphone array, and face detection based on AdaBoost is carried out using the camera. A distance and azimuth calculation model is established to obtain the position of the speaker. Second, a speaker positioning strategy based on an audio-visual bimodal combination is designed to handle different situations. Third, the path is planned by which the azimuth and distance between the robot and the speaker are maintained in a limited range. Different azimuths and distances for speaker tracking are set to perform various simulations. Finally, the mobile robot is driven to follow the path using the STM32 real-time control system. Information from the microphone array and the camera is collected and processed by Raspberry Pi.”
      原文链接:
    • NETL
    • NSTL

    New Findings Reported from University of North Carolina Chapel Hill Describe Advances in Artificial Intelligence (Smart Lattice Light-sheet Microscopy for Imaging Rare and Complex Cellular Events)

    52-53页
    查看更多>>摘要：Investigators discuss new findings in Artificial Intelligence. According to news reporting originating in Chapel Hill, North Carolina, by NewsRx journalists, research stated, “Light-sheet microscopes enable rapid high-resolution imaging of biological specimens; however, biological processes span spatiotemporal scales. Moreover, long-term phenotypes are often instigated by rare or fleeting biological events that are difficult to capture with a single imaging modality.” Financial supporters for this research include Kinship Foundation, National Institutes of Health (NIH) - USA, Searle Scholars program, Beckman Young Investigator Program, Packard Fellowship for Science and Engineering.
      原文链接:
    • NETL
    • NSTL

    New Data from Egypt-Japan University of Science and Technology Illuminate Research in Machine Learning (Tomato Quality Classification Based on Transfer Learning Feature Extraction and Machine Learning Algorithm Classifiers)

    53-54页
    查看更多>>摘要：News – Investigators publish new report on artificial intelligence. According to news reporting out of Alexandria, Egypt, by NewsRx editors, research stated, “The demand for high-quality tomatoes to meet consumer and market standards, combined with large-scale production, has necessitated the development of an inline quality grading. Since manual grading is time-consuming, costly, and requires a substantial amount of labor.” Funders for this research include Egypt-japan University of Science And Technology. The news reporters obtained a quote from the research from Egypt-Japan University of Science and Technology: “This study introduces a novel approach for tomato quality sorting and grading. The method leverages pre-trained convolutional neural networks (CNNs) for feature extraction and traditional machinelearning algorithms for classification (hybrid model). The single-board computer NVIDIA Jetson TX1 was used to create a tomato image dataset. Image preprocessing and fine-tuning techniques were applied to enable deep layers to learn and concentrate on complex and significant features. The extracted features were then classified using traditional machine learning algorithms namely: support vector machines (SVM), random forest (RF), and k-nearest neighbors (KNN) classifiers. Among the proposed hybrid models, the CNN-SVM method has outperformed other hybrid approaches, attaining an accuracy of 97.50% in the binary classification of tomatoes as healthy or rejected and 96.67% in the multiclass classification of them as ripe, unripe, or rejected when Inceptionv3 was used as feature extractor.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    New Robotics and Automation Study Results from Poznan University of Technology Described (Parameter Identifying Disturbance Rejection Control With Asymptotic Error Convergence)

    54-55页
    查看更多>>摘要：A new study on Robotics - Robotics and Automation is now available. According to news reporting originating from Poznan, Poland, by NewsRx correspondents, research stated, “In this letter, a new kind of adaptive controller for the problem of output feedback tracking is proposed on the basis of the Active Disturbance Rejection Control (ADRC) paradigm.” Financial support for this research came from Politechnika Poznanacute;ska. Our news editors obtained a quote from the research from the Poznan University of Technology, “The controller is synthesized for the systems linear in parameters by combining the classic ADRC algorithm with a recent Parameter Identifying Extended State Observer (PIESO) which employs a gradient adaptation law to actively identify the parameters of the plant. By means of the Lyapunov analysis, the asymptotic convergence of tracking, estimation, and identification errors is proved in the nominal case and the stability conditions of the closed-loop system are formulated.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    De La Salle University Researcher Adds New Study Findings to Research in Computational Intelligence (Simulated vs Actual Application of Symbiotic Model on Six Wheel Modular Multi-Agent System for Linear Traversal Mission)

    55-56页
    查看更多>>摘要：Investigators publish new report on computational intelligence. According to news reporting out of Manila, Philippines, by NewsRx editors, research stated, “Constant demand for sustainable mechanisms to perform heavy and risky tasks has driven more robotics innovations to arise.” Financial supporters for this research include Department of Science And Technology, Philippines. The news reporters obtained a quote from the research from De La Salle University: “Modular reconfigurable robotics system is one of these promising technologies that are continuously explored. Homogeneous types, to be specific, can accomplish similar missions at the same time as individual and heavier missions as an integrated system. This paper presents an analysis of the carrying capacity of a six-wheeled modular multi-agent system using the symbiotic model. The objective is to determine the resulting symbiotic relationship of a given configuration and module state combinations. The results show that the dominant relationship among the trials for linear traversal mission is commensalism. That means, the system neither benefits nor gets harmed from the symbiosis formed.”
      原文链接:
    • NETL
    • NSTL
    • Fuji Technology Press Ltd

    Research from Royal Berkshire Hospital Has Provided New Data on Artificial Intelligence (Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study)

    56-57页
    查看更多>>摘要：Fresh data on artificial intelligence are presented in a new report. According to news reporting originating from Reading, United Kingdom, by NewsRx correspondents, research stated, “IntroductionIn a drip-and-ship model for endovascular thrombectomy (EVT), early identification of large vessel occlusion (LVO) and timely referral to a comprehensive center (CSC) are crucial when patients are admitted to an acute stroke center (ASC). Several artificial intelligence (AI) decision-aid tools are increasingly being used to facilitate the rapid identification of LVO. This retrospective cohort study aimed to evaluate the impact of deploying e-Stroke AI decision support software in the hyperacute stroke pathway on process metrics and patient outcomes at an ASC in the United Kingdom.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa

    National Center for Scientific Research (CNRS) Reports Findings in Machine Learning (Unravelling abnormal in-plane stretchability of two-dimensional metal-organic frameworks by machine learning potential molecular dynamics)

    57-58页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Montpellier, France, by NewsRx correspondents, research stated, “Two-dimensional (2D) metal-organic frameworks (MOFs) hold immense potential for various applications due to their distinctive intrinsic properties compared to their 3D analogues. Herein, we designed a highly stable NiF(pyrazine) 2D MOF with a two-dimensional periodic wine-rack architecture.” Our news editors obtained a quote from the research from National Center for Scientific Research (CNRS), “Extensive first-principles calculations and molecular dynamics (MD) simulations based on a newly developed machine learning potential (MLP) revealed that this 2D MOF exhibits huge in-plane Poisson’s ratio anisotropy. This results in anomalous negative in-plane stretchability, as evidenced by an uncommon decrease in its in-plane area upon the application of uniaxial tensile strain, which makes this 2D MOF particularly attractive for flexible wearable electronics and ultra-thin sensor applications.”
      原文链接:
    • NETL
    • NSTL
    • Royal Soc Chemistry