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    'A Weapon Usage Monitoring System Having Discharge Event Monitoring Using Identification Algorithm' in Patent Application Approval Process (USPTO 20240027155)

    138-143页
    查看更多>>摘要：A patent application by the inventors Asbach, John (Laurel, MD, US); Broadway, Kyle William (Mount Airy, MD, US); Canty, Michael (Bethesda, MD, US), filed on May 9, 2023, was made available online on January 25, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents. This patent application is assigned to Armaments Research Company Inc. (Bethesda, Maryland, United States). The following quote was obtained by the news editors from the background information supplied by the inventors: "Typically, firearm tracking systems have been very limited, often requiring complex manufacturing steps in order to enable a determination of whether a weapon has been used. These systems typically have issues with reliability, have poor performance (e.g., short battery life), lack the ability to add new features, and suffer other limitations. Separately, systems for providing remote support to firearm users are also typically very limited. For example, a remote support user monitoring a deployment of firearm users within a deployment location, such as a combat zone, relies on the information reported to him or her in order to make appropriate decisions regarding providing support for those users. However, these conventional systems require a remote support user to manually analyze information about the firearm users and to manually determine how to support those firearm users, which may, in at least some cases, take more time than is available. For example, during an active fire fight between firearm users and hostile combatants, the amount of time it takes to determine to deploy reinforcements, deliver additional ammunition, or otherwise support the firearm users can dictate the success of the engagement. Accordingly, a need exists for improved systems that involve recording and tracking activities of individuals, including more advanced methods and systems for tracking discharges from firearms and more advanced methods for monitoring conditions of firearms, other assets, and users within a deployment location and automating actions to perform for remotely supporting those firearm users, such as in preparation for, during, and/or after an engagement with a hostile threat."
      原文链接:
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    Patent Issued for System and method for deploying and versioning machine learning models (USPTO 11880749)

    143-145页
    查看更多>>摘要：Capital One Services LLC (McLean, Virginia, United States) has been issued patent number 11880749, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors. The patent's inventors are Dagley, Geoffrey (McKinney, TX, US), Deshpande, Amit (McKinney, TX, US), Hoover, Jason (Grapevine, TX, US), Price, Micah (Plano, TX, US), Tang, Qiaochu (The Colony, TX, US), Vasisht, Sunil (Flowermound, TX, US), Wylie, Stephen (Carrollton, TX, US). This patent was filed on April 9, 2020 and was published online on January 23, 2024. From the background information supplied by the inventors, news correspondents obtained the following quote: "The present disclosure generally relates to a method and a system for generating a container image. "As computer technology increases, machine learning capabilities have become increasingly more important to businesses leveraging machine learning models for predictive analysis. Machine learning models include one or more machine learning algorithms that may be continuously trained with one or more training sets. The training process for the machine learning model continues until a desired accuracy level is achieved. Once the machine learning model is trained, businesses are able to input sets of data for predictive analysis."
      原文链接:
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    Researchers Submit Patent Application, 'Efficient Localization Based On Multiple Feature Types', for Approval (USPTO 20240029301)

    145-150页
    查看更多>>摘要：From Washington, D.C., NewsRx journalists report that a patent application by the inventors Koppel, Daniel Esteban (San Jose, CA, US); Steinbruecker, Frank Thomas (Mountain View, CA, US); Swaminathan, Ashwin (Dublin, CA, US); Zhou, Lipu (Sunnyvale, CA, US), filed on July 17, 2023, was made available online on January 25, 2024. The patent's assignee is Magic Leap Inc. (Plantation, Florida, United States). News editors obtained the following quote from the background information supplied by the inventors: "Localization is performed in some machine vision systems to relate the location of a device, equipped with a camera to capture images of a 3D environment, to locations in a map of the 3D environment. A new image captured by the device may be matched to a portion of the map. A spatial transformation between the new image of the matching portion of the map may indicate the "pose" of the device with respect to the map.
      原文链接:
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    Predicting the DNA binding specificity of mutated transcription factors using family-level biophysically interpretable machine learning

    150-151页
    查看更多>>摘要：According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from biorxiv.org: "Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with computational analysis have made it possible to accurately define such sequence recognition in a biophysically interpretable yet mechanismagonistic way for individual TFs. The fact that such sequence-to-affinity models are now available for hundreds of TFs provides new avenues for predicting how the DNA binding specificity of a TF changes when its protein sequence is mutated. "To this end, we developed an analytical framework based on a tetrahedron embedding that can be applied at the level of a given structural TF family.
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