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    New Robotics Study Findings Have Been Reported from Swiss Federal Institute of Technology (Robotic 3d Printing of Geopolymer Foam for Lightweight and Insulating Building Elements)

    29-30页
    查看更多>>摘要:Data detailed on Robotics have been presented. According to news reporting out of Zurich, Switzerland, by NewsRx editors, research stated, “Foam 3D printing in construction is a promising manufacturing approach that aims to reduce the amount of material, hazardous labor, and costs in producing lightweight and insulating building parts that can reduce the operational energy in buildings. Research using cement-free mineral foams derived from industrial waste showed great potential in previous studies that reduced the amount of concrete needed in composite structures.” Funders for this research include Innosuisse Impulse program, ETH Research Commission. Our news journalists obtained a quote from the research from the Swiss Federal Institute of Technology, “This article collates the latest developments in this line of work. It presents the material system with its principal components and the advanced robotic 3D printing setup with a climate-controlled fabrication chamber. Print path schemes and hybrid fabrication methods combining 3D printing and casting are evaluated. Furthermore, the article discusses the effect of different print path schemes on the thermal insulation and compressive strength performance of printed parts. A full-scale final prototype synthesizes these findings and demonstrates the fabrication of modular, lightweight, and insulating construction elements that can be assembled into monolithic wall structures. The advantages and challenges of this novel approach are elaborated on in the conclusions.”

    New Machine Learning Research from King Saud University Outlined (The Impact of the Weighted Features on the Accuracy of X-Platform's User Credibility Detection Using Supervised Machine Learning)

    30-30页
    查看更多>>摘要:Investigators publish new report on artificial intelligence. According to news reporting originating from Riyadh, Saudi Arabia, by NewsRx correspondents, research stated, “Social media represent a vital actor in our lives, often serving as a primary source of information, surpassing traditional sources. Among these platforms, the X-Platform, which used to be called Twitter, has emerged as a leading space for the exchange of opinions and emotions.” Funders for this research include Deputyship For Research And Innovation, Ministry of Education, Saudi Arabia. Our news correspondents obtained a quote from the research from King Saud University: “In this study, we introduced a supervised machine learning system designed to detect user credibility in this influential platform. User credibility detection depends largely on the features of the users on the platform. Feature weighting plays a pivotal role in identifying the significance of each feature in a dataset. It can indicate irrelevant features, which can lead to better performance in classification problems. This study aims to highlight the impact of weighted features on the accuracy of X-Platform User Credibility Detection (XUCD) using supervised machine learning methods, such as Principal Component Analysis (PCA) and correlationcoefficient algorithms, and tree-based methods, such as (ExtraTressClarifier) to extract new weighted features in the dataset and then use them to train our model to discover their impact on the accuracy of user credibility detection issues. As a result, we measured the effectiveness of different feature-weighting methods on different dataset categories to determine which obtained the best detection accuracy.”

    Great Lakes Eye Care Researcher Highlights Research in Artificial Intelligence (A Review of Intraocular Lens Power Calculation Formulas Based on Artificial Intelligence)

    31-31页
    查看更多>>摘要:Investigators publish new report on artificial intelligence. According to news reporting originating from the Great Lakes Eye Care by NewsRx correspondents, research stated, “The proper selection of an intraocular lens power calculation formula is an essential aspect of cataract surgery. This study evaluated the accuracy of artificial intelligence-based formulas.” Our news correspondents obtained a quote from the research from Great Lakes Eye Care: “Systematic review. This review comprises articles evaluating the exactness of artificial intelligence-based formulas published from 2017 to July 2023. The papers were identified by a literature search of various databases (Pubmed/MEDLINE, Google Scholar, Crossref, Cochrane Library, Web of Science, and SciELO) using the terms “IOL formulas”, “FullMonte”, “Ladas”, “Hill-RBF”, “PEARL-DGS”, “Kane”, “Karmona”, “Hoffer QST”, and “Nallasamy”. In total, 25 peer-reviewed articles in English with the maximum sample and the largest number of compared formulas were examined. The scores of the mean absolute error and percentage of patients within ±0.5 D and ±1.0 D were used to estimate the exactness of the formulas. In most studies the Kane formula obtained the smallest mean absolute error and the highest percentage of patients within ±0.5 D and ±1.0 D. Second place was typically achieved by the PEARL DGS formula. The limitations of the studies were also discussed.”

    Researchers from Shandong University Report Details of New Studies and Findings in the Area of Acute-Phase Proteins (Continual Learning for Robotic Grasping Detection With Knowledge Transferring)

    32-32页
    查看更多>>摘要:Research findings on Proteins Acute-Phase Proteins are discussed in a new report. According to news reporting originating in Jinan, People’s Republic of China, by NewsRx journalists, research stated, “Massive data-driven robotic grasping techniques require the robots to grasp a specific object conditioned on the predicted grasping postures generated from a single well-trained grasping detection network. Despite having attained near-perfect performance, two major defects still plague these networks.” Financial support for this research came from Jinan #x201C;20 New Colleges and Universities#x201D; Funded Scientific Research Leader Studio. The news reporters obtained a quote from the research from Shandong University, “First and foremost, obtaining a dataset that encompasses various grasping scenarios for training one grasping detection network is a time-consuming and labor-intensive task for researchers. Second, these grasping detection networks often exhibit poor generalization capabilities. They may not be rapidly trained using the data acquired from new scenarios, while simultaneously maintaining their previous grasping performance. In order to effectively tackle the aforementioned challenges, this article presents teacher-student architecture with a selective knowledge module to distill knowledge for continual learning in robotic grasping detection. Additionally, we refine the grasping detection network by introducing the residual feature connections to facilitate the acquisition and utilization of feature information and improve the overall performance.”

    Tiangong University Researcher Describes Recent Advances in Robotics (Cascaded Fuzzy Reward Mechanisms in Deep Reinforcement Learning for Comprehensive Path Planning in Textile Robotic Systems)

    33-34页
    查看更多>>摘要:Investigators discuss new findings in robotics. According to news reporting originating from Tianjin, People’s Republic of China, by NewsRx correspondents, research stated, “With the rapid advancement of industrial automation and artificial intelligence technologies, particularly in the textile industry, robotic technology is increasingly challenged with intelligent path planning and executing highprecision tasks.” Financial supporters for this research include Tianjin Science And Technology Bureau; Ministry of Education of The People’s Republic of China. The news correspondents obtained a quote from the research from Tiangong University: “This study focuses on the automatic path planning and yarn-spool-assembly tasks of textile robotic arms, proposing an end-to-end planning and control model that integrates deep reinforcement learning. The innovation of this paper lies in the introduction of a cascaded fuzzy reward system, which is integrated into the end-to-end model to enhance learning efficiency and reduce ineffective exploration, thereby accelerating the convergence of the model. A series of experiments conducted in a simulated environment demonstrate the model’s exceptional performance in yarn-spool-assembly tasks. Compared to traditional reinforcement learning methods, our model shows potential advantages in improving task success rates and reducing collision rates.”

    Investigators from Uppsala University Have Reported New Data on Machine Learning (The Generalizability of Machine Learning Models of Personality Across Two Text Domains)

    33-33页
    查看更多>>摘要:Researchers detail new data in Machine Learning. According to news reporting originating in Uppsala, Sweden, by NewsRx journalists, research stated, “Machine learning of high-dimensional models have received attention for their ability to predict psychological variables, such as personality. However, it has been less examined to what degree such models are capable of generalizing across domains.” Financial support for this research came from Swedish Foundation for Humanities & Social Sciences. The news reporters obtained a quote from the research from Uppsala University, “Across two text domains (Reddit message and personal essays), compared to lowdimensionaland theoretical models, atheoretical high-dimensional models provided superior predictive accuracy within but poor/non-significant predictive accuracy across domains. Thus, complex models depended more on the specifics of the trained domain. Further, when examining predictors of models, few survived across domains.”

    New Artificial Intelligence Study Findings Reported from King Faisal University (Artificial Intelligence Technologies Revolutionizing Wastewater Treatment: Current Trends and Future Prospective)

    34-35页
    查看更多>>摘要:Data detailed on artificial intelligence have been presented. According to news originating from King Faisal University by NewsRx correspondents, research stated, “Integration of the Internet of Things (IoT) into the fields of wastewater treatment and water quality prediction has the potential to revolutionize traditional approaches and address urgent challenges, considering the global demand for clean water and sustainable systems.” Funders for this research include Deanship of Scientific Research, Vice Presidency For Graduate Studies And Scientific Research, King Faisal University, Saudi Arabia. The news editors obtained a quote from the research from King Faisal University: “This comprehensive article explores the transformative applications of smart IoT technologies, including artificial intelligence (AI) and machine learning (ML) models, in these areas. A successful example is the implementation of an IoT-based automated water quality monitoring system that utilizes cloud computing and ML methods to effectively address the above-mentioned issues. The IoT has been employed to optimize, simulate, and automate various aspects, such as monitoring and managing natural systems, water-treatment processes, wastewater-treatment applications, and water-related agricultural practices like hydroponics and aquaponics. This review presents a collection of significant water-based applications, which have been combined with the IoT, artificial neural networks, or ML and have undergone critical peer-reviewed assessment.”

    New Robotics Findings Reported from Beijing Institute of Technology (Magnetic Robot for Endovascular Intervention: Performance Evaluation)

    35-36页
    查看更多>>摘要:Research findings on Robotics are discussed in a new report. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Guidewires are the most common type of interventional device used to treat vascular lesions. Magnetic robots have been developed as alternatives to the guidewire, however, most of the magnetic robot studies are qualitative experimental demonstrations uninvolved the quantitative assessment.” Financial support for this research came from Beijing Natural Science Foundation. The news correspondents obtained a quote from the research from the Beijing Institute of Technology, “This article aims to qualitatively and quantitatively assess the magnetic robot, improving the foreseeability of the tip’s deflection induced by the magnetic field. The qualitative assessment of the magnetic robot is executed through a series of experiments: circular navigation and carotid artery navigation in the vascular phantom. Based on the magnetic manipulation, the magnetically actuated robot achieves 120 degrees deflecting toward the desired direction, navigation in the tortuous pathway, and accessing the hard-toreach distal carotid artery branch. The quantitative assessment of the magnetic robot is carried out by horizontal steering and vertical steering.”

    University of Verona Reports Findings in Prostatectomy [Mirrored port placement for robotic radical prostatectomy with the Hugo RAS™ System: initial experience]

    36-37页
    查看更多>>摘要:New research on Surgery Prostatectomy is the subject of a report. According to news originating from Verona, Italy, by NewsRx correspondents, research stated, “Herein we report our first experience with Hugo RAS™ proposing a mirrored approach with different angles. Two experienced surgeons performed 10 prostatectomies (six with the standard approach and four with the mirrored one).” Our news journalists obtained a quote from the research from the University of Verona, “The median docking time was 12.5 (IQR 12-15) vs. 13.5 (IQR 12-20) minutes. The median console time was 229 (174-245) vs. 172 (IQR 164-191) minutes. None of the procedures required conversion to open surgery.” According to the news editors, the research concluded: “The study proves the versatility of the Hugo RAS™ to perform robot-assisted radical prostatectomy with two different docking angles and might be useful for novel users to adopt the preferred approach.” This research has been peer-reviewed.

    Recep Tayyip Erdogan University Reports Findings in Artificial Intelligence (Determination of growth and developmental stages in hand-wrist radiographs : Can fractal analysis in combination with artificial intelligence be used?)

    37-38页
    查看更多>>摘要:New research on Artificial Intelligence is the subject of a report. According to news reporting from Rize, Turkey, by NewsRx journalists, research stated, “The goal of this work was to assess the classification of maturation stage using artificial intelligence (AI) classifiers. Hand-wrist radiographs (HWRs) from 1067 individuals aged between 7 and 18 years were included.” The news correspondents obtained a quote from the research from Recep Tayyip Erdogan University, “Fifteen regions of interest were selected for fractal dimension (FD) analysis. Five predictive models with different inputs were created (model 1: only FD; model 2: FD and Chapman sesamoid stage; model 3: FD, age, and sex; model 4: FD, Chapman sesamoid stage, age, and sex; model 5: Chapman sesamoid stage, age, and sex). The target diagnoses were accelerating growth velocity, very high growth velocity, and decreasing growth velocity. Four AI algorithms were applied: multilayer perceptron (MLP), support vector machine (SVM), gradient boosting machine (GBM) and C 5.0 decision tree classifier. All AI algorithms except for C 5.0 yielded similar overall predictive accuracies for the five models. In order from lowest to highest, the predictive accuracies of the models were as follows: model 1<model 3<model 2<model 5<model 4. The highest overall F1 score, which was used instead of accuracy especially for models with unbalanced data, was obtained for models 1, 2, and 3 based on SVM, for model 4 based on MLP, and for model 5 based on C 5.0. Adding Chapman sesamoid stage, chronologic age, and sex as additional inputs to the FD values significantly increased the F1 score.”