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    Fudan University Reports Findings in Carcinomas (MRI-based radiomics machine lea rning model to differentiate non-clear cell renal cell carcinoma from benign ren al tumors)

    202-202页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Oncology - Carcinomas is the subject of a report. According to newsreporting originating from Fujian, People’s Republic of China, by NewsRx correspondents, research stated,“We aim to develop an MRI-based radiomics model to improve the accuracy of differentiati ng non-ccRCCfrom benign renal tumors preoperatively. The retrospective study in cluded 195 patients with pathologicallyconfirmed renal tumors (134 non-ccRCCs a nd 61 benign renal tumors) who underwent preoperative renalmass protocol MRI ex aminations.”

    Researchers at Northwest A&F University Report New Data on Machine Learning [Integrating Multi-source Remote Sensing and Machine Learning for Root-zone Soil Moisture and Yield Prediction of Winter Oilseed Rap e ( Brassica Napus L.): …]

    203-204页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. Accordingto news reporting originating from Yang ling, People’s Republic of China, by NewsRx correspondents,research stated, “Ac curately assessing root-zone soil moisture is crucial for precision irrigation, as itdirectly influences crop yield. The Temperature-Vegetation Index (Ts-VI) F eature Space, which combinesland surface temperature (Ts) and vegetation index (VI), is widely used to evaluate root-zone soil moisturein vegetated areas.”

    Findings from Sun Yat-sen University Provide New Insights into Artificial Intell igence (Employees’ Perception of Generative Artificial Intelligence and the Dark Side of Work Outcomes)

    204-205页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Artificial In telligence have been published. According tonews reporting out of Zhuhai, Peopl e’s Republic of China, by NewsRx editors, research stated, “Artificialintellige nce (as well as generative AI) has been increasingly applied in the tourism and hospitality industryand has an important impact on the work behavior of practit ioners. Drawing from the transactional theoryof stress and coping, this study i s to clarify the mechanism of potential negative impact of AI on the workoutcom es of tourism and hospitality practitioners who use generative AI (GenAI) to ass ist their work.”

    Reports Outline Machine Learning Findings from West Virginia University (Towards a Machine Learning Model To Predict the Laminar Flame Speed of Fuel Blends and Vented Gases In Lithium-ion Batteries)

    205-206页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsoriginating from Morgantown, West Vir ginia, by NewsRx correspondents, research stated, “A data-drivenmachine learnin g (ML) model for predicting laminar flame speeds (LFS) of common fuel-air mixtur es isdeveloped, with a major advantage of being convenient and prompt to be use d at various temperatures,pressures, equivalence ratios and various composition s for both single and multi-compounds fuels. Specifically,combining (ⅰ) Cantera , an open-source software for modeling chemical kinetics, thermodynamics,and tr ansport processes and (ⅱ) the regression learner model, the newly developed mod el is able to predictthe LFS for various fuels and fuel blends, including those of hydrogen, hydrocarbons such as methane,ethane, propane as well as combustib le gases from lithium-ion batteries.”

    Research from Kazimierz Wielki University in Bydgoszcz Provides New Data on Mach ine Learning (Detection of Defects in Polyethylene and Polyamide Flat Panels Usi ng Airborne Ultrasound-Traditional and Machine Learning Approach)

    206-207页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingfrom Bydgoszcz, Poland, by Ne wsRx journalists, research stated, “This paper presents the use of noncontactul trasound for the nondestructive detection of defects in two plastic plates made of polyamide(PA6) and polyethylene (PE). The aim of the study was to: (1) asses s the presence of defects as wellas their size, type, and orientation based on the amplitudes of Lamb ultrasonic waves measured in platesmade of polyamide (PA 6) and polyethylene (PE) due to their homogeneous internal structure, whichmain ly determined the selection of such model materials for testing; and (2) verify the possibilities ofbuilding automatic quality control and defect detection sys tems based on ML based on the results of theabove-mentioned studies within the Industry 4.0/5.0 paradigm.”

    Researchers Submit Patent Application, 'System and Method for an Intelligent Fra mework, Flow, and Agent', for Approval (USPTO 20240378526)

    207-211页
    查看更多>>摘要:News editors obtained the following quote from the background information suppli ed by the inventors:““Interpretation Considerations“This section describes the technical field in detail and discusses problems enc ountered in the technicalfield. Therefore, statements in the section are not to be construed as prior art.”As a supplement to the background information on this patent application, NewsRx correspondentsalso obtained the inventors’ summary information for this patent application: “The object is solved byindependent claims, and embodiments and i mprovements are listed in the dependent claims. Hereinafter,what is referred to as “aspect”, “design”, or “used implementation” relates to an “embodiment” of t heinvention and when in connection with the expression “according to the invent ion”, which designatessteps/features of the independent claims as claimed, desi gnates the broadest embodiment claimed withthe independent claims.

    Patent Application Titled 'System For Handling Separation Layers In A Production Process' Published Online (USPTO 20240375297)

    211-214页
    查看更多>>摘要:Reporters obtained the following quote from the background information supplied by the inventors:“The present invention relates to material handling systems, a nd more particularly to a system for handlingseparation layers used in a produc tion process.“During the production of mechanical components, such as for example, bearing co mponents, theprocessing of such components is often performed in automated prod uction lines. At the end of aproduction line, robot cells which palletize the p rocessed components may be provided. Depending onthe size of the components, th e components may be positioned in layers during the palletization. Duringsuch a s process, separation layers may be used in order to separate the individual com ponent layers from each other, such separation layers being typically formed as a sheet of a flexible material. These separationlayers are generally re-used an d are therefore collected and stacked after each use in order to store thelayer s in a space-saving manner until they are used once again.

    Researchers Submit Patent Application, 'Generating Training Data For Super Resol ution Models And Generating Trained Super Resolution Models', for Approval (USPT O 20240378694)

    215-219页
    查看更多>>摘要:News editors obtained the following quote from the background information suppli ed by the inventors:“With conventional image processing, it is possible to rend er images at a variety of display resolutions.This is particularly beneficial f or enabling content that is saved at one resolution to be rendered atdifferent resolutions on a plurality of different display devices having different display capabilities. Forexample, images that are saved at low resolutions can be upsc aled to higher resolutions for display onhigh-resolution displays.

    'Pull-Over Location Selection Using Machine Learning' in Patent Application Appr oval Process (USPTO 20240375684)

    219-223页
    查看更多>>摘要:The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “This specification relates to autonomous vehicl es.“Autonomous vehicles include self-driving cars, boats, and aircrafts. Autonomous vehicles use a varietyof on-board sensors and computer systems to detect nearb y objects and use such detections to makecontrol and navigation decisions.“Some autonomous vehicles have on-board computer systems that implement neural n etworks, othertypes of machine learning models, or both for various prediction tasks, e.g., object classification withinimages. For example, a neural network can be used to determine that an image captured by an on-boardcamera is likely to be an image of a nearby car.

    Patent Issued for Wafer processing tools and methods thereof (USPTO 12142513)

    223-225页
    查看更多>>摘要:News editors obtained the following quote from the background information suppli ed by the inventors:“Wafer processing tools, such as chemical mechanical polish ing (CMP) systems, may encounter delayscaused by the transfer of wafers between different processing stations. For example, processing may bedelayed as robots wait to access wafers before and/or after different processes.”As a supplement to the background information on this patent, NewsRx corresponde nts also obtainedthe inventors’ summary information for this patent: “In a firs t aspect, a wafer processing device is provided.The wafer processing device may include a wafer exchanger including two or more blades, each of the twoor more blades configured to receive a wafer, the two or more blades rotatable about an axis on a singlehorizontal plane, and the two or more blades movable between a t least a load cup and a robot accesslocation; wherein the load cup includes a wafer station that is vertically moveable relative a blade locatedin the load c up and is configured to remove a wafer from a blade located in the load cup and place awafer on a blade located in the load cup.