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    Researchers from Dalian University of Technology Describe Findings in Robotics ( Study On Material Removal and Process Optimization of Composite Material Curved Shell Components Robot Grinding Under Flexible Contact Mode)

    153-154页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Robotic s. According to news reporting from Dalian, People's Republic of China, by NewsR x journalists, research stated, "Composite material curved shell components are key parts of the new generation of high-speed aircraft and missile systems; grin ding quality of these components directly affects service performance of the equ ipment. Optimizing processing process parameters with material removal depth and surface roughness as quality targets is an effective means to improve grinding quality." Funders for this research include National Key Research & Developm ent Program of China, National Natural Science Foundation of China (NSFC), Appli ed Basic Research Program of Liaoning Province, Independent Research and Develop ment Funding Program of the First Academy, Fundamental Research Funds for the Ce ntral Universities.
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    New Machine Learning Study Findings Have Been Reported from China University of Geosciences (Hybrid Multivariate Machine Learning Models for Streamflow Forecast ing: a Two-stage Decomposition-reconstruction Framework)

    154-155页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-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 originating from Hubei, People's Rep ublic of China, by NewsRx correspondents, research stated, "Robust and accurate streamflow forecasting holds significant importance for flood mitigation, drough t warning and water resource management. On account of the intricate nonlinear a nd nonstationary nature of streamflow time series, numerous decomposition-based approaches have been proposed and integrated with other architectures." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Hubei Province.
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    Data on Machine Learning Reported by Angela J. Pereira-Morales and Colleagues (D evelopment and validation of interpretable machine learning models to predict gl omerular filtration rate in chronic kidney disease Colombian patients)

    155-156页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Bogota, Colombia, by N ewsRx correspondents, research stated, "ML predictive models have shown their ca pability to improve risk prediction and assist medical decision-making, neverthe less, there is a lack of accuracy systems to early identify future rapid CKD pro gressors in Colombia and even in South America. The purpose of this study was to develop a series of interpretable machine learning models that predict GFR at 6 -months, 9-months, and 12-months." Financial support for this research came from Science for Life.
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    Reports on Machine Learning Findings from Iowa State University Provide New Insi ghts (Timely Icu Outcome Prediction Utilizing Stochastic Signal Analysis and Mac hine Learning Techniques With Readily Available Vital Sign Data)

    156-157页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting from Ames, Iowa, by NewsRx journalists, r esearch stated, "The ICU is a specialized hospital department that offers critic al care to patients at high risk. The massive burden of ICU-requiring care requi res accurate and timely ICU outcome predictions for alleviating the economic and healthcare burdens imposed by critical care needs." The news correspondents obtained a quote from the research from Iowa State Unive rsity, "Existing research faces challenges such as feature extraction difficulti es, low accuracy, and resource-intensive features. Some studies have explored de ep learning models that utilize raw clinical inputs. However, these models are c onsidered non-interpretable black boxes, which prevents their wide application. The objective of the study is to develop a new method using stochastic signal an alysis and machine learning techniques to effectively extract features with stro ng predictive power from ICU patients' real-time time series of vital signs for accurate and timely ICU outcome prediction. The results show the proposed method extracted meaningful features and outperforms baseline methods, including APACH E IV (AUC = 0.750), deep learning-based models (AUC = 0.732, 0.712, 0.698, 0.722 ), and statistical feature classification methods (AUC = 0.765) by a large margi n (AUC = 0.869)."
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    Studies from Wuhan University of Technology Describe New Findings in Artificial Intelligence (Novel Approach to Protect Red Revolutionary Heritage Based on Arti ficial Intelligence Algorithm and Image-Processing Technology)

    157-158页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on artificial intelligence have bee n presented. According to news originating from Wuhan, People's Republic of Chin a, by NewsRx editors, the research stated, "The red revolutionary heritage is a valuable part of China's historical and cultural legacy, with the potential to g enerate economic benefits through its thoughtful development." The news journalists obtained a quote from the research from Wuhan University of Technology: "However, challenges such as insufficient understanding, lack of co mprehensive planning and layout, and limited protection and utilization methods hinder the full realization of the political, cultural, and economic value of re d heritage. To address these problems, this paper thoroughly examines the curren t state of red revolutionary heritage protection and identifies the problems wit hin the preservation process. Moreover, it proposes leveraging advanced artifici al intelligence (AI) technology to repair some damaged image data. Specifically, this paper introduces a red revolutionary cultural relic image-restoration mode l based on a generative adversarial network (GAN). This model was trained using samples of damaged image and utilizes high-quality models to restore these image s effectively."
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    Patent Application Titled 'Display Control Device And Display Control Method' Pu blished Online (USPTO 20240314288)

    158-161页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting originatin g from Washington, D.C., by NewsRx journalists, a patent application by the inve ntor MAEDA, RYO (Tokyo, JP), filed on March 7, 2024, was made available online o n September 19, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: " "Field of the Invention "The present invention relates to a display control device that controls display of a VR video, and to a display control method thereof. "Description of the Related Art "In recent years, a VR content such as a VR image (VR still image or VR video) a cquired by using a VR camera or the like is viewed via live streaming. To view t he VR content, a head mounted display (HMD) or the like is used.
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    'Systems, Methods, And Devices For Medical Image Analysis, Diagnosis, Risk Strat ification, Decision Making And/Or Disease Tracking' in Patent Application Approv al Process (USPTO 20240307016)

    161-166页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventors Earls, James P. (Alexandria, VA, US); Min, James K. (Chapel Hill, NC, US); Rodri gues Marques, Hugo Miguel (Lisbon, PT), filed on May 21, 2024, was made availabl e online on September 19, 2024, according to news reporting originating from Was hington, D.C., by NewsRx correspondents. This patent application is assigned to Cleerly Inc. (Denver, Colorado, United St ates). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "Coronary heart disease affects over 17.6 millio n Americans. The current trend in treating cardiovascular health issues is gener ally two-fold. First, physicians generally review a patient's cardiovascular hea lth from a macro level, for example, by analyzing the biochemistry or blood cont ent or biomarkers of a patient to determine whether there are high levels of cho lesterol elements in the bloodstream of a patient. In response to high levels of cholesterol, some physicians will prescribe one or more drugs, such as statins, as part of a treatment plan in order to decrease what is perceived as high leve ls of cholesterol elements in the bloodstream of the patient.
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    'Artificial Intelligence Inventory Management with Regard to Bulk/Bundled Produc ts' in Patent Application Approval Process (USPTO 20240311853)

    166-170页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventors Agrawal, Tushar (West Fargo, ND, US); Fox, Jeremy R. (Georgetown, TX, US); Raksh it, Sarbajit K. (Kolkata, IN); Rendahl, Randy A. (Raleigh, NC, US), filed on Mar ch 16, 2023, was made available online on September 19, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "The present application relates generally to an improved data processing apparatus and method and more specifically to an impro ved computing tool and improved computing tool operations/functionality for perf orming inventory management, and specifically with regard to product bundles, ba sed on artificial intelligence (AI) computer model decision support.
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    Researchers Submit Patent Application, 'Systems And Methods For Obtaining Incide nt Information To Reduce Fraud', for Approval (USPTO 20240311759)

    170-173页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-From Washington, D.C., NewsRx journali sts report that a patent application by the inventors Howard, Scott (Emeryville, CA, US); Kumar, Vinay (Fremont, CA, US); Leung, Theobolt N. (San Francisco, CA, US); Minichiello, John (Monticello, FL, US); Sanchez, Kenneth J. (San Francisco , CA, US); Struppek, Holger (San Francisco, CA, US), filed on May 24, 2024, was made available online on September 19, 2024. The patent's assignee is BlueOwl LLC (San Francisco, California, United States). News editors obtained the following quote from the background information suppli ed by the inventors: "Electronic devices are increasingly being used to automate and facilitate certain processes that conventionally require manual facilitatio n. In particular, various forms of technologies associated with the submission o f documentation are increasingly being used across various applications. For exa mple, insurance claim filings may be supplemented with digital images depicting damage to insured properties, where the images may be captured using or accessed from a variety of applications or sources.
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    'Transfer Device For Transferring Components To A Safety-Critical Production Sid e' in Patent Application Approval Process (USPTO 20240308784)

    173-177页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventor W EDE, Felix (Erding, DE), filed on February 7, 2022, was made available online on September 19, 2024, according to news reporting originating from Washington, D. C., by NewsRx correspondents. This patent application has not been assigned to a company or institution. The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "From the state of the art, in particular from a utomotive production, it is known to use production robots that can pick up orde red components and process then on a production table or similar devices. The pr oduction robots are located on a so-called production side, which must not be en tered by workers for safety reasons. The underlying problem thus consists in fee ding the components to the robot in an ordered manner without the need of worker s entering the production side.
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