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    Study Data from Aryabhatta Research Institute of Observational Sciences Provide New Insights into Machine Learning (Diversity in Fermi/GBM Gamma-Ray Bursts: New Insights from Machine Learning)

    79-80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 originating from the Aryabhatta Research Institute of Observational Sciences by NewsRx correspondents, research stated, “Classification of gamma-ray bursts (GRBs) has been a long-standing puz zle in high-energy astrophysics.” The news editors obtained a quote from the research from Aryabhatta Research Ins titute of Observational Sciences: “Recent observations challenge the traditional short versus long viewpoint, where long GRBs are thought to originate from the collapse of massive stars and short GRBs from compact binary mergers. Machine le arning (ML) algorithms have been instrumental in addressing this problem, reveal ing five distinct GRB groups within the Swift Burst Alert Telescope (BAT) light- curve data, two of which are associated with kilonovae (KNe). In this work, we e xtend our analysis to the Fermi Gamma-ray Burst Monitor catalog and identify fiv e clusters using unsupervised ML techniques, consistent with the Swift/BAT resul ts. These five clusters are well separated in the fluence-duration plane, hintin g at a potential link between fluence, duration, and complexities (or structures ) in the light curves of GRBs. Further, we confirm two distinct classes of KN-as sociated GRBs. The presence of GRB 170817A in one of the two KN-associated clust ers lends evidence to the hypothesis that this class of GRBs could potentially b e produced by binary neutron star mergers.”
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    Findings from University of Waterloo Update Understanding of Carbon Nanotubes (A Random Forest Model for Predicting and Analyzing the Performance of Cnt Tfet Wi th Highly Doped Pockets)

    80-81页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on Nanotechnolog y - Carbon Nanotubes. According to news reporting originating in Waterloo, Canad a, by NewsRx journalists, research stated, “This paper presents a Random Forest (RF) machine learning model that relates the DC characteristics and high-frequen cy response of a carbon nanotube (CNT) tunnel field-effect transistor (TFET) wit h highly doped pockets to the transistor parameters. The analysis of multiple fa ctors for a complex structure as the one studied here becomes expensive with the ordinary simulation techniques and hence machine learning (ML) offers a profici ent method to model and enhance the understanding of the key factors that influe nce the CNT TFET with pockets in considerably reduced time.” The news reporters obtained a quote from the research from the University of Wat erloo, “Numerical simulations are used to generate the data on which the model i s trained. This dataset comprises ten input features and four output attributes. The tuned model is capable of predicting the output characteristics of the devi ce with minimal mean squared error (MSE). The RF model is also compared to other ML algorithms to demonstrate its advantage. This study makes use of the interpr etable random forest model in identifying the key factors that affect the output characteristics of the Carbon nanotube TFET with highly doped pockets.”
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    Patent Issued for Coating system for coating an optical substrate, method thereo f and coated optical substrate (USPTO 12103325)

    81-83页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting originatin g from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Ko enig, II, Jerry L. (Largo, FL, US), filed on September 7, 2017, was published on line on October 1, 2024. The assignee for this patent, patent number 12103325, is Transitions Optical Ltd . (Tuam, Ireland). Reporters obtained the following quote from the background information supplied by the inventors: “Field of the Invention “The present invention relates to an apparatus and method for coating an optical article. In particular, the present invention relates to an inkjet coater for a pplying a coating to the optical article and a method of using the inkjet coater to coat the optical article.
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    Patent Application Titled 'Dynamic Fact Contextualization In Support Of Artifici al Intelligence (Ai) Model Development' Published Online (USPTO 20240330577)

    83-86页
    查看更多>>摘要：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 ntors Hampp-Bahnmueller, Thomas (Stuttgart, DE); Hind, Michael (Cortlandt Manor, NY, US); Piorkowski, David John (White Plains, NY, US); Richards, John Thomas ( Honeoye Falls, NY, US), filed on March 30, 2023, was made available online on Oc tober 3, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: “Embodiments of the invention relate to dynamic fact contextua lization in support of AI model development. In particular, embodiments of the i nvention relate to dynamic fact contextualization of AI documentation in support of AI model development. “With AI model development, facts are gathered throughout the AI lifecycle and u sed to generate a FactSheet. However, as the facts are gathered throughout the A I model lifecycle, fact producers are not able to easily see the current state o f fact collection and how that relates to eventual documentation as a FactSheet.
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    Patent Issued for Computer implemented method for the automated analysis or use of data (USPTO 12106059)

    86-90页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – From Alexandria, Virginia, NewsRx jour nalists report that a patent by the inventors Curran, Finlay (Cambridgeshire, GB ), Heywood, Robert (Cambridgeshire, GB), Roscoe, Harry (Cambridgeshire, GB), Tun stall-Pedoe, William (Cambridgeshire, GB), filed on November 22, 2023, was publi shed online on October 1, 2024. The patent’s assignee for patent number 12106059 is Unlikely Artificial Intellig ence Limited (Cambridgeshire, United Kingdom). News editors obtained the following quote from the background information suppli ed by the inventors: “1. Field of the Invention “The field of the invention relates to a computer implemented method for the aut omated analysis or use of data; one implementation is a voice assistant that is able to analyse, interpret and act on natural language spoken and text inputs. “2. Technical Background “Natural language (NL) is language evolved for humans such as the English langua ge. Although significant advances have been made in computers’ ability to proces s natural language, computers are still not able to deeply understand the meanin g of natural language and use that meaning internally. “For this reason most computer applications typically use structured data to sto re information that they need for processing-e.g. a relational database: designi ng the schema, populating the database and writing code to process the fields in the database.
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    Patent Issued for Tactile robotic training platform (USPTO 12103182)

    91-93页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A patent by the inventors Bibl, Andrea s (Los Altos, CA, US), Golda, Dariusz (Portola Valley, CA, US), Harjee, Nahid (S unnyvale, CA, US), Pavate, Vikram (Foster City, CA, US), Weisberg, David (Mill V alley, CA, US), filed on February 9, 2024, was published online on October 1, 20 24, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents. Patent number 12103182 is assigned to Tacta Systems Inc. (Palo Alto, California, United States). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Field “This disclosure relates generally to robotic control and, more specifically, to a tactile robotic training platform. Other aspects are also described. “Background Information “A robotic device, or robot, may refer to a machine that can automatically perfo rm one or more actions or tasks in an environment. For example, a robotic device could be configured to assist with manufacturing, assembly, packaging, maintena nce, cleaning, transportation, exploration, surgery, or safety protocols, among other things. A robotic device can include various mechanical components, such a s a robotic arm and an end effector, to interact with the surrounding environmen t and to perform the tasks. A robotic device can also include a processor or con troller executing instructions stored in memory to configure the robotic device to perform the tasks.”
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    Patent Issued for Garage door opener battery backup system (USPTO 12104423)

    94-97页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting originatin g from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Di llon, Gerald (Escondido, CA, US), Learmonth, Darren (Austin, TX, US), Mattson, M ark C. (Carlsbad, CA, US), Niemela, Jari (San Diego, CA, US), filed on October 6 , 2021, was published online on October 1, 2024. The assignee for this patent, patent number 12104423, is Nice North America LLC (Carlsbad, California, United States). Reporters obtained the following quote from the background information supplied by the inventors: “Garage door opening systems are configured to open or close a utomatically a garage door in response to a trigger from a remote control. A con ventional garage door opening system includes control electronics and a motor to control movement of the garage door. This motor and accompanying control electr onics is driven by a power supply. To provide reliable power, many automatic doo rs include a power supply coupled with a battery backup that switches in when th e power source is compromised.”
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    Patent Issued for Real-time predictions based on machine learning models (USPTO 12106199)

    97-100页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Salesforce Inc. (San Francisco, Califo rnia, United States) has been issued patent number 12106199, according to news r eporting originating out of Alexandria, Virginia, by NewsRx editors. The patent’s inventors are Bansal, Kaushal (Pleasanton, CA, US), Dasgupta, Amrit a (San Francisco, CA, US), Jagota, Arun Kumar (Sunnyvale, CA, US), Karanth, Rake sh Ganapathi (San Mateo, CA, US). This patent was filed on April 20, 2023 and was published online on October 1, 2 024. From the background information supplied by the inventors, news correspondents o btained the following quote: “Field of Art “This disclosure relates in general to machine learning based models, and in par ticular to performing real-time tasks using predictions using machine learning b ased models. “Description of the Related Art “Several online systems, for example, multi-tenant systems use machine learning based models for making predictions. These machine learning based models are inv oked by applications that may execute on client devices. Furthermore, for certai n applications, a multi-tenant system may generate scores using the machine lear ning based models on a periodic basis, for example, once every hour or once a da y. The multi-tenant system provides the results of execution of the machine lear ning based models to the client device. The multi-tenant system provides the gen erated scores to the users of the tenants for invoking via their applications. T his allows the use of powerful hardware of the multi-tenant system to execute th e machine learning based model while incurring low communication overhead while transmitting the generated results to the client devices. Such techniques are su ited for applications that do not require results of the machine learning models in real-time. However, such systems are inadequate if the results of execution of the machine learning based model are needed in real-time. For example, a clie nt device may not be able to generate accurate results immediately in response t o changes in the features used as input. The user is required to wait until the execution of the model is triggered on a periodic basis.
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    Patent Application Titled 'Adaptive Learning For Semantic Segmentation' Publishe d Online (USPTO 20240331368)

    100-103页
    查看更多>>摘要：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 ntors Cremieux, Matthias (Paris, FR); Salman, Nader (Houston, TX, US), filed on October 27, 2022, was made available online on October 3, 2024. No assignee for this patent application has been made.Reporters obtained the following quote from the background information supplied by the inventors: “Machine learning automation of data inspection tasks (e.g., m anufacturing asset imaging, satellite imagery, seismic imaging, medical imaging, etc.) using various imaging modalities (RGB, Infrared, Multi- Spectral . . . ) a nd employing precise pixel level labeling typically includes a bottleneck at the labeling stage. In the inspection domain, large amounts of data may be generate d, but most of the data is not readily used for machine learning purposes. That is, the data is unlabeled, and labeling the data generally calls for human subje ct matter experts to label the high-resolution images at a per pixel level. Vari ous techniques have been used to increase the efficiency of this task (e.g., wat er shedding), but it remains a time-intensive activity that increases the costs for such automation projects.”
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    Researchers Submit Patent Application, 'Method Of Searching For An Optimal Combi nation Of Hyperparameters For A Machine Learning Model', for Approval (USPTO 202 40330774)

    103-108页
    查看更多>>摘要：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 Huang, He (Paris, FR); Wol from, Basile (La Garde, FR), filed on April 1, 2024, was made available online o n October 3, 2024. No assignee for this patent application has been made. News editors obtained the following quote from the background information suppli ed by the inventors: “Machine learning is a branch of artificial intelligence th at enables a computing system to learn from data, without having been explicitly programmed to perform a given task. “Machine learning enables a machine to acquire knowledge and skills from a set o f data, in order to make predictions, classifications or other types of processi ng operations on new data. “A machine learning model is a mathematical representation of a system or proces s that enables a machine to learn from data.
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