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    Study Results from University of Vienna in the Area of Machine Learning Reported (Constraint Free Physics-informed Machine Learning for Micromagnetic Energy Min imization)

    127-127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 out of Vienna, Austria, by NewsRx editors, research stated, “We introduce a novel method for micromagnetic energy minimization which uses physics -informed neural networks to find a magne tic configuration which minimizes the Gibbs Free energy functional without the n eed of any constraint optimization framework. The Cayley transform is applied to a neural network to assure that the model output lives on the Lie group of rota tion matrices SO(3).” Funders for this research include Austrian Science Fund (FWF), Vienna Scientific Cluster (VSC), Austrian Science Fund (FWF).
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    Researchers from Nanyang Technological University Report Recent Findings in Mach ine Learning (A Robust Evaluating Strategy of Tunnel Deterioration Using Ensembl e Machine Learning Algorithms)

    128-128页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Machine Lea rning. According to news reporting out of Singapore, Singapore, by NewsRx editor s, research stated, “Tunnels are crucial for transportation networks, necessitat ing regular inspection and structural deterioration evaluation to ensure their o perational capacity. Previously, only traditional models have been developed to characterize the overall degradation of tunnels and with data shuffling the mode ls trained ignore the utilization of historical data for future scenarios.” Financial supporters for this research include National Research Foundation, Sin gapore under its AI Singapore Programme (AISG), Ministry of Education Tier 1 Gra nts, Singapore, Nanyang Technological University.
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    Researcher’s Work from National Institute of Advanced Industrial Science and Tec hnology (NIAIST) Focuses on Machine Learning (Merits and Demerits of Machine Lea rning of Ferroelectric, Flexoelectric, and Electrolytic Properties of Ceramic .. .)

    129-130页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Nagoya, Japan, by NewsRx editors, research stated, “In the present review, the merits and deme rits of machine learning (ML) in materials science are discussed, compared with first principles calculations (PDE (partial differential equations) model) and p hysical or phenomenological ODE (ordinary differential equations) model calculat ions.” Funders for this research include Japan Science And Technology Agency.
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    New Findings from University of Pavia Describe Advances in Machine Learning (How Fair Is Machine Learning In Credit Lending?)

    129-129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 Ma chine Learning. According to news reporting from Pavia, Italy, by NewsRx journal ists, research stated, “Machine learning models are widely used to decide whethe r to accept or reject credit loan applications. However, similarly to human-base d decisions, they may discriminate between special groups of applicants, for ins tance based on age, gender, and race.” The news correspondents obtained a quote from the research from the University o f Pavia, “In this paper, we aim to understand whether machine learning credit le nding models are biased in a real case study, that concerns borrowers asking for credits in different regions of the United States. We show how to measure model fairness using different metrics, and we explore the capability of explainable machine learning to add further insights.”
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    New Artificial Intelligence Study Findings Have Been Reported by Investigators a t Indian Institute of Technology (IIT) Bhubaneswar (Artificial Intelligence-base d Visual Inspection System for Structural Health Monitoring of Cultural Heritage )

    130-131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 Artificial Intell igence are discussed in a new report. According to news reporting originating in Odisha, India, by NewsRx journalists, research stated, “The United Nations aims to preserve, evaluate, and conserve cultural heritage (CH) structures as part o f sustainable development. The design life expectancy of many CH structures is s lowly approaching its end.” The news reporters obtained a quote from the research from the Indian Institute of Technology (IIT) Bhubaneswar, “It is thus imperative to conduct frequent visu al inspections of CH structures following conservation guidelines to ensure thei r structural integrity. This study implements a custom defect detection, and loc alization supervised deep learning model based on the you only look once (YOLO) v5 real-time object detection algorithm by implementing a case study of the Dadi -Poti tombs in Hauz Khas Village, New Delhi. The custom YOLOv5 model is trained to automatically detect four defects, namely, discoloration, exposed bricks, cra cks, and spalling, and tested on a dataset comprising 10291 images. The validity and performance of the custom YOLOv5 model are compared with a ResNet 101 archi tecture-based faster region-based convolutional neural network (R-CNN), and conv entional manual visual inspection methods are used to convey the significance of the developed artificial intelligence-based model.”
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    Findings from Zhengzhou University of Light Industry in the Area of Machine Lear ning Described (A Fault-tolerant and Scalable Boosting Method Over Vertically Pa rtitioned Data)

    131-132页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting out of Zhengzhou, People’s R epublic of China, by NewsRx editors, research stated, “Vertical federated learni ng (VFL) can learn a common machine learning model over vertically partitioned d atasets. However, VFL are faced with these thorny problems: (1) both the trainin g and prediction are very vulnerable to stragglers; (2) most VFL methods can onl y support a specific machine learning model.” Funders for this research include Guangxi Science and Technology Major Project, National Natural Science Foundation of China (NSFC), Key scientific research pro ject of colleges and universities in Henan Province.
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    Researchers from National University of Singapore Report on Findings in Robotics (Primp: Probabilistically-informed Motion Primitives for Efficient Affordance L earning From Demonstration)

    132-133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 Robotics. According to news originating from Singapore, Singapore, by NewsRx cor respondents, research stated, “This article proposes a Learning-from- Demonstrati on (LfD) method using probability densities on the workspaces of robot manipulat ors. The method, named PRobabilistically-Informed Motion Primitives (PRIMP), lea rns the probability distribution of the end effector trajectories in the 6-D wor kspace that includes both positions and orientations.” Financial support for this research came from NUS Startup.
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    Capital Medical University Reports Findings in Scoliosis (Accuracy and postopera tive assessment of robot-assisted placement of pedicle screws during scoliosis s urgery compared with conventional freehand technique: a systematic review and .. .)

    133-134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 Musculoskeletal Diseas es and Conditions - Scoliosis is the subject of a report. According to news orig inating from Beijing, People’s Republic of China, by NewsRx correspondents, rese arch stated, “A systematic review and meta-analysis. The complexity of human ana tomical structures and the variability of vertebral body structures in patients with scoliosis pose challenges in pedicle screw placement during spinal deformit y correction surgery.” Financial supporters for this research include National Natural Science Foundati on of China, Beijing Municipal Natural Science Foundation.
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    Investigators from University of Coimbra Release New Data on Robotics (Robots At Work: New Evidence With Recent Data)

    134-134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 from Coimbra, Portugal, by NewsRx jou rnalists, research stated, “We reassess the relationship between robotization an d the growth in labor productivity with more recent data. We discover that the e ffect of robot density in the growth productivity substantially decreased in the post-2008 period.” Financial support for this research came from Fundacao para a Ciencia e a Tecnol ogia (FCT). The news correspondents obtained a quote from the research from the University o f Coimbra, “In this period, the lower positive effect of robot density in the gr owth of labor productivity is less dependent on the increase in value added. The data analysis dismisses any positive effect of robotization on hours worked. Re sults are confirmed by several robustness checks, cross-sectional (and panel-dat a) Instrumental Variable and quantile regression analysis. By means of the quant ile regression analysis, we learn that the effect of robots on labor productivit y is stronger for low productivity sectors and that in the most recent period, t he effect of robotization felt significantly throughout the distribution.”
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    Rio de Janeiro State University Reports Findings in Leptospirosis (Study of mach ine learning techniques for outcome assessment of leptospirosis patients)

    135-135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 Gram-Negative Bacteria l Infections - Leptospirosis is the subject of a report. According to news repor ting out of Rio de Janeiro, Brazil, by NewsRx editors, research stated, “Leptosp irosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficien cies. Its symptoms are often confused with other syndromes, which can compromise clinical diagnosis and the failure to carry out specific laboratory tests.” Our news journalists obtained a quote from the research from Rio de Janeiro Stat e University, “In this respect, this paper presents a study of three algorithms (Decision Tree, Random Forest and Adaboost) for predicting the outcome (cure or death) of individuals with leptospirosis. Using the records contained in the gov ernment National System of Aggressions and Notification (SINAN, in portuguese) f rom 2007 to 2017, for the state of Par?, Brazil, where the temporal attributes o f health care, symptoms (headache, vomiting, jaundice, calf pain) and clinical e volution (renal failure and respiratory changes) were used. In the performance e valuation of the selected models, it was observed that the Random Forest exhibit ed an accuracy of 90.81% for the training dataset, considering the attributes of experiment 8, and the Decision Tree presented an accuracy of 74.2 9 for the validation database. So, this result considers the best attributes poi nted out by experiment 10: time first symptoms medical attention, time first sym ptoms ELISA sample collection, medical attention hospital admission time, headac he, calf pain, vomiting, jaundice, renal insufficiency, and respiratory alterati ons.”
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