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    Researchers Submit Patent Application, 'Multi-Spectral Imaging Systems For Asses sing Health', for Approval (USPTO 20240180452)

    119-124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 Ali, Mohamed M. (St. Paul, MN, US); Lelicoff, Nancy (Fair Oaks, CA, US); Skinner, Cathy (St. Paul, MN, US) ; Welcher, Rosanne (Ventura, CA, US), filed on April 13, 2022, was made availabl e online on June 6, 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: "Patients with chronic illnesses (e.g., cancer) make freque nt visits to healthcare facilities. The purpose of these visits may be for routi ne treatments and/or health assessments that provide a snapshot of the patient's health. One common assessment involves a blood analysis, which is useful for ev aluating treatment efficacy and/or identifying potential side effects of a drug. "To facilitate frequent treatments, some patients are provided with a port-cathe ter, i.e., a port. Ports are small medical devices implanted under the patient's skin to provide convenient access to the circulatory system for drug delivery. Ports generally do not require any maintenance. However, ports do occasionally f ail, break, or leak fluid. As such, ports must be routinely inspected at healthc are facilities to ensure proper function.
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    Patent Issued for Cleaning roller for cleaning robots (USPTO 11998151)

    124-126页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-iRobot Corporation (Bedford, Massachus etts, United States) has been issued patent number 11998151, according to news r eporting originating out of Alexandria, Virginia, by NewsRx editors. The patent's inventors are Blouin, Matthew (Townsend, MA, US), Goddard, William (Somerville, MA, US). This patent was filed on March 28, 2022 and was published online on June 4, 2024 . From the background information supplied by the inventors, news correspondents o btained the following quote: "An autonomous cleaning robot can navigate across a floor surface and avoid obstacles while vacuuming the floor surface to ingest d ebris from the floor surface. The cleaning robot can include rollers to pick up the debris from the floor surface. As the cleaning robot moves across the floor surface, the robot can rotate the rollers, which guide the debris toward a vacuu m airflow generated by the cleaning robot. In this regard, the rollers and the v acuum airflow can cooperate to allow the robot to ingest debris. During its rota tion, the roller can engage debris that includes hair and other filaments. The f ilament debris can become wrapped around the rollers."
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    Patent Issued for 3D modeling based on neural light field (USPTO 12002146)

    127-130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 Chai, Menglei (Los Angeles, CA, US ), Huang, Zeng (Los Angeles, CA, US), Olszewski, Kyle (Los Angeles, CA, US), Ren , Jian (Marina Del Ray, CA, US), Tulyakov, Sergey (Marina del Rey, CA, US), Wang , Huan (Somerville, MA, US), filed on March 28, 2022, was published online on Ju ne 4, 2024. The patent's assignee for patent number 12002146 is Snap Inc. (Santa Monica, Cal ifornia, United States). News editors obtained the following quote from the background information suppli ed by the inventors: "Three-dimensional (3D) reconstruction from multiple two-di mensional (2D) images is the creation of a 3D model from a set of images. This p rocess usually involves receiving 2D images from several points of view and then reconstructing a 3D model based on those images. The 3D models can be used to s imulate a 3D view of a real-world environment to generate different experiences, such as augmented reality and virtual reality experiences."
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    'Discrete Roller Assembly-Based Helical Drive For Translation' in Patent Applica tion Approval Process (USPTO 20240183428)

    130-135页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent application by the inventors Livingston, Daniel (Hayward, CA, US); Ozog, Stefan (Winnipeg, CA); Thable, Gagan deep (Calgary, CA), filed on December 6, 2023, was made available online on June 6, 2024, according to news reporting originating from Washington, D.C., by News Rx 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: "A conventional threaded rod and nut mechanism c an provide a motion transmission that can be used to mechanically translate a pa yload (e.g., a robot) along an axis. When the nut is split radially into a numbe r of sections, each section could act upon the threaded rod (also referred to as a "threaded shaft" and "screw") similar to a conventional worm gear by contacti ng and applying force to the nut at only a portion of the thread's circumference . As an example, a worm gear mated to a rack to form a conventional worm drive c an be used to move a robot coupled to the worm gear upward or downward along a v ertical axis in a controlled manner. Such a conventional worm gear can produce a sliding frictional drag force (e.g., friction between a worm gear and a toothed wheel or frame) during operation of the worm gear. In a conventional worm drive , the sliding frictional force is proportional to a torque transmitted by the wo rm gear to the rack. Further, using a worm gear to lift a payload (e.g., a robot included in an automated storage and retrieval system (AS/RS)) relative to a fr ame (e.g., rack) can generate an additional fixed frictional drag force from a w eight of the payload. This frictional drag force can contribute large power loss es and provide added wear to worm drive components. By conservation of energy, t his power is transformed primarily into heat, which can contribute to material p roperty degradation and risk human safety associated with devices and/or machine s that incorporate the worm drive components.
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    Patent Application Titled 'Smart Home Automation Using Multi- Modal Contextual In formation' Published Online (USPTO 20240187687)

    135-139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 Chandra, Ashwin (Santa Clara, CA, US); Chung, David Ho Suk (Rancho Palos V erdes, CA, US); Ortega Pena, Andres Leonardo de Jesus (San Jose, CA, US); Yoon, Suk-Un (Suwon-si, KR), filed on December 1, 2022, was made available online on J une 6, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: "Smart televisions are being used in more and more households across the world. Smart televisions are often centrally-located within household s and have large display screens. As a result, smart televisions are becoming th e preferred hub for visual information, configuration, and automation of smart h ome devices. For example, smart televisions can be used to support user task ini tiation and monitoring for smart home automation functions."
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    Patent Issued for Autonomous gladhands coupling systems, devices, and methods (U SPTO 11999206)

    139-142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 Knizhnik, Gedaliah (Silver Spring, MD, US), Lacaze, Alberto (Potomac, MD, US), Murphy, Karl (Cocoa Beach, FL, US), Rotundo, Steven (Baltimore, MD, US), filed on April 26, 2023, was published onl ine on June 4, 2024. The patent's assignee for patent number 11999206 is Robotic Research OpCo LLC (C larksburg, Maryland, United States). News editors obtained the following quote from the background information suppli ed by the inventors: "An 18-wheeler or tractor-trailer truck includes a semi-tra iler (also referred to herein as "trailer") releasably coupled to a tractor (als o referred to herein as "truck" or "vehicle"). At distribution centers, marine t erminals, rail heads, etc., the trailer is often disconnected from the truck, fo r example, for cargo loading, cargo unloading, storage, or changing between truc ks. In such locations, rather than the truck used for road hauling, the trailer can be moved about by a specialized local tractor (also referred to herein as "h ostler," "hostler truck," "yard truck," "yard dog," "terminal tractor," "shuttle truck," or "shunt truck"). However, trailers have a pneumatic parking brake (al so referred to "spring brake" or "emergency brake") that mechanically engage whe n the tractor's pressurized pneumatic lines are disconnected (e.g., via gladhand couplers on the trailer). Thus, to allow movement of the trailer by the hostler , the trailer parking brake has to be disengaged by pressurizing the pneumatic l ines. This requires manually connecting pneumatic lines between hostler and the trailer, as automatic connection tends to be difficult or subject to failure. No t only does manual connection of pneumatic lines require additional time and sub ject a user to potential risk, but it also limits the adoption of automation (e. g., automating operation of the hostler to move trailers) at such locations. Emb odiments of the disclosed subject matter may address one or more of the above-no ted problems and disadvantages, among other things."
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    Evaluation of Machine Learning Models for Aqueous Solubility Prediction in Drug Discovery

    143-143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 based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Determining the aqueous solubility of the chemical compound is of great importa nce in-silico drug discovery. "However, correctly and rapidly predicting the aqueous solubility remains a chal lenging task. "This paper explores and evaluates the predictability of multiple machine learni ng models in the aqueous solubility of compounds. Specifically, we apply a serie s of machine learning algorithms, including Random Forest, XGBoost, LightGBM, an d CatBoost, on a well-established aqueous solubility dataset (i. e., the Huuskon en dataset) of over 1200 compounds. Experimental results show that even traditio nal machine learning algorithms can achieve satisfactory performance with high a ccuracy. "In addition, our investigation goes beyond mere prediction accuracy, delving in to the interpretability of models to identify key features and understand the mo lecular properties that influence the predicted outcomes.
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