期刊,Robotics & Machine Learning Daily News 2024年卷Oct.3期_国家学术搜索

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Patent Application Titled 'Event Optimization In A Multi-Tenant Computing Enviro nment' Published Online (USPTO 20240311696)

215-220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 ntors Chiu, Anthony (Manchester, GB); Krishnaswamy, Arun (San Ramon, CA, US); Mu khopadhyay, Dibya (Oakland, CA, US); Pitchumani, Vinodhini (Tamil Nadu, IN); Sha ik, Amanulla (Tamil Nadu, IN); Sooklaris, Maria Nicoletta (San Francisco, CA, US ); Sudersanam, Sumithra (Tamil Nadu, IN), filed on April 30, 2024, was made avai lable online on September 19, 2024. No assignee for this patent application has been made.

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Patent Issued for Defect management apparatus, method and nontransitory compute r readable medium (USPTO 12094098)

220-222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 by the inventors Ike, Tsukasa (Tokyo, JP), Imoto, Kazunori (Kawasaki, JP), Nakai, Tomohiro (Kawasaki, JP), fi led on February 26, 2021, was published online on September 17, 2024, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondent s. Patent number 12094098 is assigned to Kabushiki Kaisha Toshiba (Tokyo, Japan). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "In a manufacturing processing for semiconductor s or the like, defect management is important to accurately monitor the manufact uring quality and improve the yield. Because inspection data in defect managemen t is enormous and the inspection items include many different items, the work of manually checking the inspection data is not easy. For this reason, in recent y ears, machine learning have been used in defect management, and classification m odels of determining the type of the defect from inspection images have attracte d attention.

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Researchers Submit Patent Application, 'Implement Management System For Determin ing Implement State', for Approval (USPTO 20240312204)

222-226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 Anderson, Noel W. (Fargo, ND, US); Maeder, Curtis A. (Johnston, IA, US); Runde, Jeffrey E. (Cedar Falls, I A, US); Schleicher, Tyler D. (Ankeny, IA, US), filed on May 22, 2024, was made a vailable online on September 19, 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: "Operators of a farming vehicle conventionally monitor the implements such as plows or sprayers pulled by farming vehicle by periodically c hecking the implement by looking at the implement from the cabin of the farming vehicle. An implement naturally wears over time as operations are performed, and operators conventionally monitor the implement for wear during operation. An im plement may be worn out to a point where a component of the implement falls from the implement while the vehicle operates. In addition to monitoring the wear of the implement, the operator of a conventionally operated farming vehicle may mo nitor the state of the implement. Some implements are not designed to be in a ce rtain state in combination with operating the farming vehicle in a particular wa y. For example, a tractor operator may check if the shanks of a plow are raised before putting the tractor in reverse. The shanks can be attached to the plow su ch that their rotational motion is limited to a fixed range. If the shanks are n ot raised when the vehicle travels in reverse, they may break or dislodge from t he vehicle.

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'Robot With Smart Path Planning For Multiple Parts' in Patent Application Approv al Process (USPTO 20240308070)

227-231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 R obertson, Taylor L. (Kitchener, CA), filed on October 12, 2023, was made availab le online on September 19, 2024, according to news reporting originating from Wa shington, 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: "Programming motion trajectories of a robot (e.g ., a collaborative robot or an industrial robot) prior to actual welding or cutt ing can be quite complicated. In addition to the challenges associated with prog ramming a weld trajectory (welding path) along a weld joint, other challenges as sociated with programming an ingress trajectory toward a weld joint (e.g., on an other part) and an egress trajectory away from a weld joint (e.g., on a part) ex ist. Furthermore, it can be laborious to duplicate weld program info for a seque nce of identical parts to be welded."

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Patent Issued for Device control using audio data (USPTO 12093607)

231-233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 Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Ch en, Xin (Torrance, CA, US), Monastyrshyn, Yurii (Santa Monica, CA, US), Poliakov , Fedir (Marina Del Rey, CA, US), Vij, Shubham (Los Angeles, CA, US), filed on J uly 29, 2022, was published online on September 17, 2024. The assignee for this patent, patent number 12093607, is Snap Inc. (Santa Monica , California, United States). Reporters obtained the following quote from the background information supplied by the inventors: "Some computers have limited computational resources. For exam ple, smartphones generally have a relatively small screen size, limited input/ou tput controls, and less memory and processor power than their desktop computer a nd laptop counterparts. Different issues arise when interacting with a computer with limited computational resources. For example, a user may have to drill-down into a number of menus instead of using a keyboard shortcut or simply viewing a ll the menus at once on a larger screen (e.g., a screen of a desktop). Further, navigating to different user interfaces, different menus, and selecting differen t user interface elements can be computationally intensive, which can cause the device to lag and further unnecessarily drain the device's battery."

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'Flow Reactor System And Flow Reaction Method' in Patent Application Approval Pr ocess (USPTO 20240307842)

234-236页

查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A patent application by the inventors BASH, Danii l (Singapore, SG); BUONASSISI, Tonio (Singapore, SG); CHELLAPPAN, Vijila (Singap ore, SG); CHENG, Jian Wei Jayce (Singapore, SG); HIPPALGAONKAR, Kedar (Singapore , SG); KUMAR, Jatin (Singapore, SG); LIM, Yee Fun (Singapore, SG); WONG, Swee Li ang (Singapore, SG); XU, Yang (Singapore, SG), filed on July 20, 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: "Designing new materials with desired output cha racteristics or properties involves multiple stages of materials and process dev elopment cycles. For example, flow reactor systems work on the principle of flow chemistry to synthesise new materials. Flow chemistry is a well-established tec hnique wherein streams of fluids are continuously flowed, and if the fluids are reactive, a chemical reaction takes place and a new compound is formed. However, currently available flow reactor systems focus mainly on synthesising new mater ials, and the characterization of the new materials is done separately. The curr ent approach of synthesising and characterising new materials is tedious and ine ffective and has low throughput.

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Patent Issued for Method, device, and computer program product for managing mach ine learning model (USPTO 12093553)

236-239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 Alexandria, Virginia, NewsRx jour nalists report that a patent by the inventors Chen, Qiang (Shanghai, CN), Jia, Z hen (Shanghai, CN), Liu, Jinpeng (Shanghai, CN), Ni, Jiacheng (Shanghai, CN), Sh a, Danqing (Shanghai, CN), filed on May 14, 2021, was published online on Septem ber 17, 2024. The patent's assignee for patent number 12093553 is EMC IP Holding Company LLC ( Hopkinton, Massachusetts, United States). News editors obtained the following quote from the background information suppli ed by the inventors: "With development of computer technologies in recent years, the Internet of Things (IoT) has been increasingly applied in various aspects o f people's lives. A core in the Internet of Things technology is analysis of dat a obtained from Internet of Things devices (e.g., various temperature sensors, p osition sensors, image sensors, meters, etc.), and these sensor data can be used to implement corresponding intelligent control functions based on technologies related to artificial intelligence. In order to implement intelligent control fu nctions, it is necessary, for example, to upgrade a version of a machine learnin g model. Future data is then processed by using the upgraded machine learning mo del. However, there are still many problems to be solved in the process of upgra ding the machine learning model."

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Patent Application Titled 'Guiding A User Of An Artificial Reality System To A P hysical Object Having A Trackable Feature Using Spatial Audio Cues' Published On line (USPTO 20240310175)

239-242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 ntors Ananthabhotla, Ishwarya (Cambridge, MA, US); Balsam, Nava K.(Woodinville, WA, US); Ihlefeld, Antje (Redmond, WA, US); Johnson, Khia (Seattle, WA, US); Sa lehi, Haniyeh (Statesville, NC, US), filed on March 15, 2023, was made available online on 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: "This disclosure relates generally to artificial reality syste ms, and more specifically to guiding a user of an artificial reality system to a physical object having a trackable feature using spatial audio cues. "When physical objects (e.g., car keys, phones, wallets, remote controls, etc.) are lost or misplaced, several techniques are commonly used to locate them. For example, if a physical object was recently in an individual's possession, the in dividual may retrace their steps and look for the object as they do so. As an ad ditional example, an individual may think about their location the last time the y saw a physical object they have lost or misplaced and look for it at the locat ion. As yet another example, if an individual is searching for a mobile device a nd the device has a remote locating application installed on it, the application may allow the individual to view location information for the device on another device (e.g., a laptop computer).

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Machine learning-optimized targeted detection of alternative splicing

242-243页

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Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from mult i-channel audio

243-243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 based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Understanding the behavioral and neural dynamics of social interactions is a go al of contemporary neuroscience. Many machine learning methods have emerged in r ecent years to make sense of complex video and neurophysiological data that resu lt from these experiments. Less focus has been placed on understanding how anima ls process acoustic information, including social vocalizations. "A critical step to bridge this gap is determining the senders and receivers of acoustic information in social interactions. While sound source localization (SS L) is a classic problem in signal processing, existing approaches are limited in their ability to localize animal-generated sounds in standard laboratory enviro nments. Advances in deep learning methods for SSL are likely to help address the se limitations, however there are currently no publicly available models, datase ts, or benchmarks to systematically evaluate SSL algorithms in the domain of bio acoustics. Here, we present the VCL Benchmark: the first large-scale dataset for benchmarking SSL algorithms in rodents.

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