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| | + | '''Summary of the patent applications from Microsoft Technology Licensing, LLC on October 5th, 2023''' |
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| | + | Microsoft Technology Licensing, LLC has recently filed patents for various technologies in different fields. These patents cover thermal management devices, eye imaging systems, video encoding rate control using reinforcement learning, gaze adjustment in video conferences, DNS updates for service instances, privacy protection for streaming post analytics, secure uploading of file-system tree structures, digital wallet authentication and verifiable claims, and automatic offloading of applications to a cloud service provider. |
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| | + | Notable patent applications include: |
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| | + | * A thermal management device consisting of a heat spreader and a folded graphite sheet to collect and release heat efficiently. |
| | + | * A camera system with multiple lenses for capturing detailed and accurate images of the eye in a near-eye system. |
| | + | * A solution for rate control in video encoding using reinforcement learning to improve real-time communication quality while reducing computation overhead. |
| | + | * Methods and systems for adjusting the gaze of participants in a video conference to match their desired eye gaze direction. |
| | + | * A method for updating a domain name system dynamically based on the status indicator of service instances in a microservice architecture. |
| | + | * A technology that ensures privacy for event-level data in streaming post analytics by applying a differential privacy mechanism to protect user interactions. |
| | + | * A computer method for encrypting and decrypting transport packets using fixed and public keys for secure network debugging. |
| | + | * A method for securely scanning and mitigating security and privacy risks in content uploaded to a storage cloud provider using proxy services. |
| | + | * A process involving a digital wallet, identification provider, and verifiable claim issuer for generating and requesting verifiable claims using authentication tokens and decentralized identifiers. |
| | + | * A system that automatically offloads applications from on-premises servers to a cloud service provider to handle spikes in resource demand. |
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| | + | These recent patent filings demonstrate Microsoft Technology Licensing, LLC's commitment to innovation and development across various technological domains. |
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| | ==Patent applications for Microsoft Technology Licensing, LLC on October 5th, 2023== | | ==Patent applications for Microsoft Technology Licensing, LLC on October 5th, 2023== |
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| | '''Inventor''' | | '''Inventor''' |
| | Paolo COSTA | | Paolo COSTA |
| − |
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| − | '''Brief explanation'''
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| − | The abstract describes a method of making a multi-core polymer optical fiber. The process involves arranging preforms of the fiber in a stack and then drawing and bonding them together to create the final fiber. This method helps to prevent contaminants or impurities from affecting the signal transmission through the fiber cores and also reduces crosstalk between the cores. The abstract also mentions that a multi-core polymer optical fiber can be obtained using this method.
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| − |
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| − | '''Abstract'''
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| − | A method of fabricating a multi-core polymer optical fibre comprises arranging optical fibre preforms in a stack, the optical fibre preforms each comprising a polymer core and polymer cladding surrounding the polymer core; and drawing and bonding the stack to form the multi-core polymer optical fibre. Any contaminants or impurities which collect on outer surfaces of the preforms may be confined to boundaries between the preforms, which may avoid attenuation of signals passed through the cores while at the same time reducing crosstalk between cores of the final manufactured fibre. Also provided is a multi-core polymer optical fibre obtainable by the method.
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| | ===AUTHENTICATION ASSAY USING EMBEDDED DEOXYRIBONUCLEIC ACID TAGGANTS (17657120)=== | | ===AUTHENTICATION ASSAY USING EMBEDDED DEOXYRIBONUCLEIC ACID TAGGANTS (17657120)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Yuan-Jyue CHEN | | Yuan-Jyue CHEN |
| − |
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| − | '''Brief explanation'''
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| − | This abstract describes a method for authenticating products using DNA taggants. The method involves using a substrate with multiple assay locations, each containing a reporter oligonucleotide. The reporter oligonucleotide has three regions: a toehold sequence, a universal sequence, and a unique sequence. The sample collected from the product contains DNA taggants labeled with fluorophores that are complementary to the reporter oligonucleotide. When the sample is incubated with the substrate, a DNA strand displacement reaction occurs, replacing the complementary strand with the fluorophore-labeled DNA taggant. Exciting the fluorophore produces light emitted at the assay locations, creating a unique pattern that can be used for authentication.
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| − |
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| − | '''Abstract'''
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| − | An authentication assay using embedded deoxyribonucleic acid (DNA) taggants includes a substrate and a sample of an authenticity label collected from a product. The substrate has a plurality of assay locations, each of which includes a reporter oligonucleotide bound to the substrate. The reporter oligonucleotide includes a first region with a single-stranded toehold sequence, a second region with a universal sequence, and a third region with a unique sequence, the second and third regions being prehybridized with a complementary strand. The sample includes at least one fluorophore-labeled DNA taggant complementary to the first and second regions of the reporter oligonucleotide. Incubation of the substrate with the sample results in a toehold-mediated DNA strand displacement reaction that exchanges the complementary strand for the fluorophore-labeled DNA taggant. Excitation of the fluorophore molecule attached to the DNA taggant produces a pattern of light emitted at one or more assay locations.
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| | ===TARGETED TEMPORAL ALD (17708511)=== | | ===TARGETED TEMPORAL ALD (17708511)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Ville Kalevi SAUNAJOKI | | Ville Kalevi SAUNAJOKI |
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| − | '''Brief explanation'''
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| − | The abstract describes a device called targeted temporal ALD, which is used for applying a thin film coating to specific areas of products or substrates. The device consists of an ALD head that has an outer housing and an inner housing. The inner housing has ports for connecting precursor gas and inert gas sources. The precursor gases are applied to the targeted areas of the products from an inner chamber, while inert gases are applied to an outer chamber to control where the precursor gases are applied. Some versions of the device can also move the ALD head in different directions relative to the products.
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| − | '''Abstract'''
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| − | A targeted temporal ALD device includes an ALD head that is configured to perform targeted ALD to discrete targeted areas of products/substrates positioned on the mounting surface(s) of the ALD device. The ALD head includes: (i) an outer housing; (ii) an inner housing positioned within the outer housing; and (ii) a plurality of ports formed into the inner housing and outer housing for connecting at least one precursor gas source and at least one inert gas source to the ALD head. The precursor gases are applied to targeted areas of the products/substrates from an inner chamber in the inner housing, while inert gases are applied to an outer chamber between the inner and outer housings to limit/control application of the precursor gases to a desired target area. Some targeted temporal ALD devices are also configured to position/reposition the ALD head in three orthogonal directions relative to product(s)/mounting surface(s).
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| | ===CRYOGENIC REMOVAL OF CARBON DIOXIDE FROM THE ATMOSPHERE (17828692)=== | | ===CRYOGENIC REMOVAL OF CARBON DIOXIDE FROM THE ATMOSPHERE (17828692)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Benjamin Franklin CUTLER | | Benjamin Franklin CUTLER |
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| − | '''Brief explanation'''
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| − | CryoDAC is a method that uses extremely low temperatures to remove carbon dioxide (CO2) from the atmosphere. It works by cooling the air and passing it over a surface that is even colder. This causes the CO2 to freeze into a solid while other gases like oxygen and nitrogen remain as gases. The frozen CO2 is then collected and stored, while the cold air without CO2 is returned to the atmosphere. This process can be done using a cryogenic refrigerator to cool the surface.
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| − | '''Abstract'''
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| − | Cryogenic removal of carbon dioxide from the atmosphere, or CryoDAC (Cryogenic Direct Air Capture), uses extremely low temperatures to convert atmospheric COinto a frozen solid while other components of air such as oxygen and nitrogen remain as gases. Air from the atmosphere is passed through a recuperative heat exchanger to cool the air to a temperature slightly above the deposition point of CO. The cooled air is then passed over a deposition surface chilled to a temperature below the deposition point of CO. Carbon dioxide in the air transitions from gas to solid form upon contact with the deposition surface. The frozen COis collected and stored. The cold air with COremoved is passed back through the recuperative heat exchanger to cool incoming air and is then returned to the atmosphere. The deposition surface may be cooled by a cryogenic refrigerator.
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| | ===MULTI-CORE OPTICAL FIBRE AND FABRICATION THEREOF (17710961)=== | | ===MULTI-CORE OPTICAL FIBRE AND FABRICATION THEREOF (17710961)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Paolo COSTA | | Paolo COSTA |
| − |
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| − | '''Brief explanation'''
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| − | The abstract describes a type of optical fiber that has multiple cores embedded in a polymer cladding. The cladding has a specific shape that makes it easier to align the cores with light sources or detectors. The abstract also mentions that optical cables and kits including this type of fiber are provided, as well as a method for fabricating it.
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| − | '''Abstract'''
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| − | A multi-core optical fibre comprises a plurality of cores embedded in cladding. The cladding comprises a polymer. The cladding has an outer cross-sectional shape with an order of rotational symmetry of less than or equal to 4. By limiting the rotational symmetry of the multi-core optical fibre, rotational alignment of the cores with light sources/light detectors may be made easier. Also provided are optical cables and kits including the multi-core optical fibre, and a method of fabricating a multi-core polymer optical fibre.
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| | ===GRADED-INDEX POLYMER OPTICAL FIBRE AND THE FABRICATION THEREOF (17710926)=== | | ===GRADED-INDEX POLYMER OPTICAL FIBRE AND THE FABRICATION THEREOF (17710926)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Paolo COSTA | | Paolo COSTA |
| − |
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| − | '''Brief explanation'''
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| − | The abstract describes a method for making a graded-index polymer optical fiber. The process involves creating a cladding composition using a mixture of a cladding polymer and a dopant. The cladding is then formed around a core made of a different polymer. The dopant is then diffused into the core, creating a concentration gradient where the dopant concentration increases as you move away from the center of the core. This helps to reduce the optical attenuation of the fiber. The abstract also mentions that a graded-index polymer optical fiber can be obtained using this method.
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| − | '''Abstract'''
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| − | A method of fabricating a graded-index polymer optical fibre comprises preparing a cladding composition, the cladding composition comprising either a mixture of a cladding polymer and a dopant or a mixture of a cladding polymer precursor and a dopant; forming cladding from the cladding composition around a core, the core comprising a core polymer; and causing diffusion of the dopant into the core such that the dopant has a continuous concentration gradient, according to which concentration gradient the concentration of the dopant increases with radial distance from a centre of the core. The dopant is a compound having a refractive index which is lower than a refractive index of the core polymer. By distributing the dopant such that the dopant concentration is lowest at the centre of the core, the optical attenuation of the graded-index polymer optical fibre may be reduced. Also provided is a graded-index polymer optical fibre obtainable by the method.
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| | ===Light Shield for MEMS Scanner (17711639)=== | | ===Light Shield for MEMS Scanner (17711639)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Di SUN | | Di SUN |
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| − | '''Brief explanation'''
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| − | The abstract describes a device that consists of a mirror connected to a block of semiconductor material through flexible beams. The mirror can rotate around an axis along the beams, and a piezoresistive sensor is attached to one of the beams to measure the angle of rotation. The device also includes a light blocking shield to cover the exposed parts of the semiconductor block around the mirror.
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| − | '''Abstract'''
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| − | A device includes a mirror coupled via a pair of flexible beams supported by a block of semiconductor material that has a cavity about the mirror and beams to allow the mirror to rotate about an axis along the beams. A piezoresistive sensor is coupled to one of the beams to provide information representative of an angle of rotation of the mirror. A light blocking shield covers exposed portions of the block of semiconductor material about the mirror.
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| | ===EYE-IMAGING SYSTEM WITH SWITCHABLE HOT MIRRORS (17657883)=== | | ===EYE-IMAGING SYSTEM WITH SWITCHABLE HOT MIRRORS (17657883)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Benjamin Eliot LUNDELL | | Benjamin Eliot LUNDELL |
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| − | '''Brief explanation'''
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| − | The abstract describes a system that uses a series of switchable hot mirrors in an eye-imaging system. The system includes a head-mounted display with a camera that captures images of the eye. The switchable hot mirrors are designed to direct the reflected light from the eye towards the camera. A controller is used to control the reflectivity of each mirror.
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| − | '''Abstract'''
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| − | Examples are disclosed that relate to using an array of hot mirrors in an eye-imaging system. One example provides a head-mounted display system, comprising a frame, an eye-imaging camera supported on the frame, a switchable hot mirror array comprising a plurality of switchable hot mirrors configured to direct light reflecting from an eye toward the eye-imaging camera, and a controller configured to control switching of a reflectivity of each of the plurality of switchable hot mirrors.
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| | ===POLARIZATION-RECYCLING WAVEGUIDED ILLUMINATION SYSTEM FOR MICRODISPLAY (17710910)=== | | ===POLARIZATION-RECYCLING WAVEGUIDED ILLUMINATION SYSTEM FOR MICRODISPLAY (17710910)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Ishan CHATTERJEE | | Ishan CHATTERJEE |
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| − | '''Brief explanation'''
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| − | This abstract describes a system that enhances the efficiency of illuminating non-emissive polarization-sensitive microdisplays, such as Liquid Crystal on Silicon (LCoS) displays. The system uses a waveguide to direct light from an unpolarized source to the microdisplay. At the same time, it recycles light with the incorrect polarization for the microdisplay, improving the overall efficiency of the illumination. The polarization recycling can occur at different stages, including the input coupler, the waveguide itself, or the output coupler.
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| − | '''Abstract'''
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| − | An illumination system for non-emissive polarization-sensitive microdisplays such as LCoS is implemented in a waveguide that guides illumination light from an unpolarized source to the microdisplay while simultaneously recycling light of the wrong polarization for the microdisplay to improve illumination efficiency. Polarization recycling may be performed at one or more of an input coupler that in-couples illumination light to the waveguide, the waveguide itself, or an output coupler that out-couples the illumination light from the waveguide to the microdisplay.
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| | ===TIR PRISMS AND USE OF BACKLIGHT FOR LCOS MICRODISPLAY ILLUMINATION (18330448)=== | | ===TIR PRISMS AND USE OF BACKLIGHT FOR LCOS MICRODISPLAY ILLUMINATION (18330448)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Ishan CHATTERJEE | | Ishan CHATTERJEE |
| − |
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| − | '''Brief explanation'''
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| − | The abstract describes a display engine designed for a head-mounted display (HMD) device. It uses a reflective liquid crystal on silicon (LCoS) spatial light modulator (SLM) that is illuminated by a backlight module. The display engine also includes a pair of optical prisms that enable total internal reflection (TIR). In a mixed-reality application, the prisms guide light from the backlight module to the LCoS SLM and project virtual images reflected from the SLM. These images are then directed through projection optics and viewed by the user through a diffractive waveguide combiner.
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| − | '''Abstract'''
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| − | A display engine adapted for use in a head-mounted display (HMD) device includes a reflective liquid crystal on silicon (LCoS) spatial light modulator (SLM) that is illuminated using a backlight illumination module and a pair of optical prisms providing a total internal reflection (TIR) function. In an illustrative mixed-reality embodiment, the TIR prism pair guides light to the LCoS SLM from the backlight illumination module and projects virtual images reflected from the LCoS SLM, through projection optics, to a diffractive waveguide combiner for viewing by an HMD user.
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| | ===MODULAR POWER AND/OR FUNCTIONALITY ON WEARABLE DEVICE (17657725)=== | | ===MODULAR POWER AND/OR FUNCTIONALITY ON WEARABLE DEVICE (17657725)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Jouya JADIDIAN | | Jouya JADIDIAN |
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| − | '''Brief explanation'''
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| − | The abstract describes a wearable device that includes a frame, internal charge storage, a module interface, and an electrical connector. The frame supports the wearable device on a user, while the internal charge storage is located within the frame. The module interface is also located on the frame, and it allows for the attachment of a detachable module. The detachable module can be replaced while the wearable device is being worn, without needing to power it down. The wearable device can be operated using the internal charge storage.
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| − | '''Abstract'''
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| − | Examples are disclosed that relate to a battery and a functional module on a detachable module. One example provides a wearable device comprising a frame configured to support the wearable device on a user, internal charge storage located within the frame, a module interface located on the frame, and an electrical connector located within the module interface to electrically connect to a detachable module positioned in the module interface such that that detachable module is replaceable while being worn without powering down the wearable device by operating the wearable device using the internal charge storage.
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| | ===COMPUTING DEVICE HINGE WITH SLIDING COVER (17706078)=== | | ===COMPUTING DEVICE HINGE WITH SLIDING COVER (17706078)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Luke SCHWARTZEL | | Luke SCHWARTZEL |
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| − | '''Brief explanation'''
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| − | This abstract discusses the use of hinges in computing devices and the need to provide a continuous visual impression to the user. It explains that achieving a 360-degree range of motion with conventional hinges is difficult and often results in a variable gap between the hinges and the components. The abstract introduces a technology that uses mechanically deterministic sliding covers to conceal these gaps while still allowing for a full range of motion.
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| − | '''Abstract'''
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| − | Hinged computing devices often connect two components via one or more hinges, using either a door-hinge style or other conventional hinge style. Presenting a continuous visual impression of the computing device to the user, with any gaps covered, provides protection to internal components and suggests a higher overall quality of the computing device to the user. Using conventional hinges, achieving a 360-degree range of motion is difficult, and often requires a pair of hinges connected by a spine to accommodate the respective thicknesses of the two hinged components in all orientations. However, using a pair of conventional hinges connected by a spine to achieve a 360-degree range of motion can yield a variable gap between the spine and the hinged components. The presently disclosed technology is directed to mechanically deterministic sliding covers that conceal these variable gaps, while still maintaining a 360-degree range of motion of the computing device.
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| | ===ADAPTIVE POWER CONTROL FOR AN ELECTRONIC DEVICE (17691374)=== | | ===ADAPTIVE POWER CONTROL FOR AN ELECTRONIC DEVICE (17691374)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Donghwi KIM | | Donghwi KIM |
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| − | '''Brief explanation'''
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| − | The abstract describes a method for controlling the power distribution from a charger to an energy storage device and hardware elements in an electronic device. The method involves determining if the current between the charger and the energy storage device meets a charging condition, based on the direction and magnitude of the current. It also determines if the power consumed by the hardware elements meets a system power condition, based on a set system power limit. The method then adjusts the power consumption of the hardware elements within a predefined range of system power limits, based on the satisfaction of the charging condition and the power supply condition.
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| − | '''Abstract'''
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| − | A method of adaptively controlling the distribution of power supplied by a charger of an electronic device between an energy storage device and one or more hardware elements is provided. The method includes determining whether current communicated between the charger of the electronic device and the energy storage device satisfies a charging condition, the charging condition based on one or more of a direction of the current communicated and a magnitude of the current communicated, determining whether consumed system power consumed by the hardware elements satisfies a system power condition based on a determined system power limit, and adjusting power consumption of the one or more hardware elements of the electronic device to consume a different consumed system power within a predefined range of system power limits, based at least in part on satisfaction of the charging condition and satisfaction of the power supply condition.
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| | ===INTELLIGENT PLACEMENT OF A BROWSER-ADDED USER INTERFACE ELEMENT ON A WEBPAGE (17710334)=== | | ===INTELLIGENT PLACEMENT OF A BROWSER-ADDED USER INTERFACE ELEMENT ON A WEBPAGE (17710334)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Sushanth RAJASANKAR | | Sushanth RAJASANKAR |
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| − | '''Brief explanation'''
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| − | This abstract describes a browser that can intelligently place a user interface (UI) element on a webpage in a way that it looks integrated with the webpage, rather than just being overlaid on top of it. The placement is done in a way that doesn't block important content or interfere with the functionality of the webpage. The browser does this after retrieving the webpage from a web server, so it doesn't have control over the layout and appearance of the webpage. The UI element can be a selectable element associated with a specific function, such as image-based search.
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| − | '''Abstract'''
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| − | Disclosed herein a browser that intelligently places a user interface (UI) element on a webpage such that the UI element appears to be integrated and coordinated with the webpage and not merely overlaid on the webpage. The intelligent placement ensures that the UI element neither obstructs the view of pertinent content displayed via the webpage nor interferes with the functionality of the webpage. Moreover, the intelligent placement ensures that the UI element is completely visible to a user. The placement of the UI element is done by the browser after the webpage has been retrieved from a web server. Consequently, the browser lacks the ability to control or alter the layout and appearance of the webpage. The UI element can be a selectable UI element that the browser associates with a function. In one example, the function can be an image-based search.
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| | ===SHARING MULTIPLE APPLICATIONS IN UNIFIED COMMUNICATION (17708868)=== | | ===SHARING MULTIPLE APPLICATIONS IN UNIFIED COMMUNICATION (17708868)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Neeraj Surana | | Neeraj Surana |
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| − | '''Brief explanation'''
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| − | This abstract describes a method and system for managing the presentation of multiple applications during a unified communication session. The system receives a selected set of applications from a first participant and displays them to one or more second participants. Only one application from the selected set is shown at a time, and the system switches between different applications based on the most recent selection or user interaction.
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| − | '''Abstract'''
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| − | A method and system for managing presentation of multiple applications from a first participant to one or more second participants of a unified communication session are described herein, including receiving, from the first participant, a selected set of applications for display to the one or more second participants during the unified communication session and causing only one of the selected set of applications to be displayed at a time to the one or more second participants through the meeting application, including switching between causing first and second applications of the selected set of applications to be displayed to the one or more second participants based on a most recent selection or user interaction with the first and second applications.
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| | ===MAINTAINING A RECORD DATA STRUCTURE USING PAGE METADATA OF A BOOKKEEPING PAGE (17710914)=== | | ===MAINTAINING A RECORD DATA STRUCTURE USING PAGE METADATA OF A BOOKKEEPING PAGE (17710914)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Jan-Ove Almli KARLBERG | | Jan-Ove Almli KARLBERG |
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| − | '''Brief explanation'''
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| − | This abstract describes a method for processing data operation requests and performing operations on pages of a record data structure. The method involves generating a data operation based on a received request, which includes a bookkeeping page identifier. The bookkeeping page of the record index structure is identified using this identifier, along with an index page of the record index structure that has a parameter of the data operation. If the timestamp in the metadata of the identified index page matches the corresponding timestamp in the metadata of the bookkeeping page, the data operation is performed on the identified index page. This method allows for the use and maintenance of large data indexes in data storage systems, even when data entries expire over time due to automatic temporal compaction processes.
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| − | '''Abstract'''
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| − | The disclosure herein describes processing data operation requests and performing associated operations on pages of a record data structure. A data operation is generated based on a received data operation request. The data operation request includes a bookkeeping page identifier. A bookkeeping page of the record index structure is identified based on the bookkeeping page identifier and an index page of the record index structure with a parameter of the data operation. If a timestamp in metadata of the identified index page matches a corresponding timestamp associated with the identified index page in metadata of the bookkeeping page, the data operation is performed on the identified index page. The disclosure enables the use and maintenance of large data indexes in data storage systems where data entries expire over time due to automatic temporal compaction processes.
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| | ===NATIVELY-INTEGRATED APPLICATION CONTENT CUSTOMIZATION FOR ENTERPRISES (17713081)=== | | ===NATIVELY-INTEGRATED APPLICATION CONTENT CUSTOMIZATION FOR ENTERPRISES (17713081)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Jesse H. STEIN | | Jesse H. STEIN |
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| − | '''Brief explanation'''
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| − | This abstract describes systems and methods for customizing application content at an enterprise level. It involves executing enterprise applications on a remote computing system and providing a user interface for customizing content during application execution. Users can specify parameters for generating enterprise-specific customized content, which is then displayed on the remote computing system.
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| − | '''Abstract'''
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| − | Systems and methods for providing enterprise-level application content customization are described herein. A method includes executing an enterprise application (from a suite of enterprise applications that are utilized by the enterprise) on a remote computing system operated by an enterprise administrator. The method includes surfacing a content customization UI on a display device of the remote computing system during execution of the enterprise application. The content customization UI includes UI elements that enable the specification of parameters for providing enterprise-specific customized content during execution of enterprise application(s) from the suite of enterprise applications on remote computing system(s) operated by enterprise user(s). The method also includes receiving, via the content customization UI, user input including the specification of parameters and generating the customized content based on the specified parameters. The method further includes surfacing the customized content on display device(s) of the remote computing system(s) during execution of the enterprise application(s).
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| | ===COMPILATION AND EXECUTION OF SOURCE CODE AS SERVICES (18206725)=== | | ===COMPILATION AND EXECUTION OF SOURCE CODE AS SERVICES (18206725)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | Robert Lovejoy GOODWIN | | Robert Lovejoy GOODWIN |
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| − | '''Brief explanation'''
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| − | This document discusses a method for converting source code into services. The method involves taking input source code, analyzing it to identify data dependencies and immutability points, and then converting parts of the code after the immutability points into service modules. The goal is to simplify the code and improve its efficiency by breaking it down into smaller, independent modules.
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| − | '''Abstract'''
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| − | This document relates to compilation of source code into services. One example method involves receiving input source code, identifying data dependencies in the input source code, and identifying immutability points in the input source code based at least on the data dependencies. The example method also involves converting at least some of the input source code occurring after the immutability points to one or more service modules.
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| | ===SCALABLE BEHAVIORAL INTERFACE SPECIFICATION CHECKING (17708611)=== | | ===SCALABLE BEHAVIORAL INTERFACE SPECIFICATION CHECKING (17708611)=== |
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| | '''Inventor''' | | '''Inventor''' |
| | John Lawrence SINGLETON | | John Lawrence SINGLETON |
| − |
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| − | '''Brief explanation'''
| |
| − | This abstract describes a computer system that can analyze a codebase, which includes both source code and specifications of how the code should behave. The system can identify specific parts of the code where a method is called, gather information about the parameters being passed to that method, and find the specifications associated with that method. These specifications include a precondition that describes the expected behavior of the method. The system then analyzes the method using the specifications and the parameter information to determine if the method deviates from the expected behavior. Finally, the system presents the analysis results in a visual format.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A computer system is configured to analyze a codebase containing source code and specification of intended behavior of at least a portion of the source code. The analysis of the codebase identifies a callsite of a method within the codebase, obtains a set of bounds associated with one or more parameters being passed to the method at the callsite, and identifies a set of specification associated with the method. The set of specification includes at least a precondition specifying an intended behavior of the method. The method is then analyzed based on the set of specifications and the set of bounds to determine whether the method deviates from the intended behavior specified by the precondition. The computer system then visualizes a result based on analyzing the method.
| |
| | | | |
| | ===COMPUTING RESOURCE MANAGEMENT WITH FAST SORTING USING VECTOR INSTRUCTIONS (17712879)=== | | ===COMPUTING RESOURCE MANAGEMENT WITH FAST SORTING USING VECTOR INSTRUCTIONS (17712879)=== |
| Line 214: |
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| | '''Inventor''' | | '''Inventor''' |
| | Conor John CUNNINGHAM | | Conor John CUNNINGHAM |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract discusses how computing resource management can be improved during fast sorting using vector instructions. It explains the process of determining a pivot value and position in a data set, and then determining whether moving data in the sampled portion can be avoided. This determination is based on factors such as whether the data is already sorted or constant-valued. By leveraging this determination, unnecessary data movement can be avoided, leading to more efficient sorting. The abstract also mentions the selection of a sorting instruction implementation based on the microarchitecture version of the computing device. Additionally, it discusses the use of a soft 3-way quicksort technique, which involves finding adjacent data elements with the same pivot value and adding a partition boundary at the end of these elements.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Computing resource management is improved during fast sorting using vector instructions. The process includes: determining a pivot value and a pivot position in a data set (e.g., by sampling with vectors and determining the sample median), determining whether moving data in the sampled portion may be avoided (e.g., if it is constant-valued or already sorted) and, leveraging that determination to possibly avoid unnecessary data movement, sorting the data set. Some examples further determine the microarchitecture version of the computing device performing the sorting and select an implementation of sorting instruction that is tuned for that microarchitecture version (e.g., based on the number of vector registers and motherboard cache configuration). Some examples leverage a soft 3-way quicksort by finding data elements adjacent to the pivot position that also have the pivot value and adding a partition boundary at the end of the set of same-valued data elements.
| |
| | | | |
| | ===DYNAMICALLY-CONFIGURABLE BASEBOARD MANAGEMENT CONTROLLER (18329062)=== | | ===DYNAMICALLY-CONFIGURABLE BASEBOARD MANAGEMENT CONTROLLER (18329062)=== |
| Line 225: |
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| | '''Inventor''' | | '''Inventor''' |
| | Bryan D. KELLY | | Bryan D. KELLY |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for configuring a baseboard management controller (BMC) to monitor the state of a server. The BMC is provided with a configuration schema that specifies which devices of the server should be monitored and includes additional configuration details for each device. The BMC then performs a discovery sequence to check if the devices are connected to it. If successful, the BMC starts monitoring the devices. If unsuccessful, an error is issued to alert the appropriate personnel to fix the issue.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to dynamically configure a baseboard management controller to monitor a state of a server. For example, a configuration schema may be provided to the baseboard management controller. The configuration schema specifies each of the devices of the server that is to be monitored by the baseboard management controller. The configuration schema also specifies additional configuration details with respect to each of the devices. Based on the configuration information included in the configuration schema, the baseboard management controller performs a discovery sequence with respect to each of the devices to verify that such devices are communicatively coupled to the baseboard management controller. If the discovery sequence is successful, the baseboard management controller begins monitoring the devices. However, if the discovery sequence is unsuccessful, the baseboard management controller issues an error, thereby enabling the proper personnel to remediate the issue.
| |
| | | | |
| | ===SUPPORT OF VIRTUAL NETWORK AND NON-VIRTUAL NETWORK CONNECTIVITY ON THE SAME VIRTUAL MACHINE (18327713)=== | | ===SUPPORT OF VIRTUAL NETWORK AND NON-VIRTUAL NETWORK CONNECTIVITY ON THE SAME VIRTUAL MACHINE (18327713)=== |
| Line 236: |
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| | '''Inventor''' | | '''Inventor''' |
| | Vishal TANEJA | | Vishal TANEJA |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a hybrid state for a virtual machine (VM) in a cloud computing system. This hybrid state allows the VM to communicate with other VMs within a virtual network (VNET VMs) while also maintaining connectivity with VMs outside of the virtual network (non-VNET VMs).
| |
| − |
| |
| − | To achieve this, a non-VNET VM can be transitioned into a hybrid VM that operates in a hybrid state. The hybrid VM is assigned a private virtual IP address (VNET address) for communication with other VNET VMs. However, it continues to use a physical IP address to communicate with non-VNET VMs.
| |
| − |
| |
| − | This allows the hybrid VM to maintain connectivity with non-VNET VMs even after it has been migrated to the VNET. A network stack is configured to process data packets differently depending on whether they are destined for non-VNET VMs or VNET VMs.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A hybrid state for a virtual machine (VM) in a cloud computing system enables a VM to communicate with other VMs that belong to a virtual network (VNET VMs) while maintaining connectivity with other VMs that do not belong to the virtual network (non-VNET VMs). A non-VNET VM can be transitioned to a hybrid VM that operates in a hybrid state. The hybrid VM can be assigned a private virtual IP address (VNET address) for communication with other VNET VMs. The hybrid VM can continue to use a physical IP address to communicate with other non-VNET VMs. In this way, the hybrid VM is able to maintain connectivity with other non-VNET VMs during and after migration to the VNET. A network stack can be configured to process data packets that are destined for non-VNET VMs differently from data packets that are destined for VNET VMs.
| |
| | | | |
| | ===PREDICTIVE QUOTA MANAGEMENT FOR CLOUD CUSTOMERS (17709993)=== | | ===PREDICTIVE QUOTA MANAGEMENT FOR CLOUD CUSTOMERS (17709993)=== |
| Line 251: |
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| | '''Inventor''' | | '''Inventor''' |
| | Banafsheh SAMAREH ABOLHASANI | | Banafsheh SAMAREH ABOLHASANI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | A cloud compute resource provider has developed a method to automatically adjust the amount of compute resources allocated to a customer's subscription. This method involves analyzing the customer's recent usage data, determining if a historical usage model has been trained for their subscription, and if so, using that model to predict future resource usage. Based on this prediction, the method suggests an adjusted resource quota that will optimize the utilization of the customer's subscription.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A cloud compute resource provider implements a method for automatically adjusting a quota of compute resources allocated to an individual customer subscription. The method includes determining a current usage metric for the individual customer subscription for a recent time interval; determining whether a subscription-based historical usage model has been trained on historical usage data of the individual customer subscription; and responsive to determining that the subscription-based historical usage model has been trained, executing the subscription-based historical usage model to generate a future resource usage metric predicting a usage of the customer subscription over a future time interval; and outputting a recommended adjusted resource quota for the individual subscription, the predicted future resource usage metric satisfying a target utilization of the recommended adjusted resource quota.
| |
| | | | |
| | ===ADDRESSING FOR DISAGGREGATED MEMORY POOL (18024590)=== | | ===ADDRESSING FOR DISAGGREGATED MEMORY POOL (18024590)=== |
| Line 262: |
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| | '''Inventor''' | | '''Inventor''' |
| | Siamak TAVALLAEI | | Siamak TAVALLAEI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for mapping memory addresses in a disaggregated memory system. In this system, a compute node provides a range of host physical addresses (HPAs) that correspond to different parts of the memory pool allocated to the node. These HPAs are then converted into a contiguous range of device physical addresses (DPAs). Each DPA is mapped to a specific physical element in the memory pool based on a target address decoder (TAD) that is determined by a slice identifier and a slice-to-TAD index. This mapping process allows for efficient access to the memory in the disaggregated system.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method for memory address mapping in a disaggregated memory system includes receiving an indication of one or more ranges of host physical addresses (HPAs) from a compute node of a plurality of compute nodes, the one or more ranges of HPAs including a plurality of memory addresses corresponding to different allocation slices of the disaggregated memory pool that are allocated to the compute node. The one or more ranges of HPAs are converted into a contiguous range of device physical addresses (DPAs). For each DPA, a target address decoder (TAD) is identified based on a slice identifier and a slice-to-TAD index. Each DPA is mapped to a media-specific physical element of a physical memory unit of the disaggregated memory pool based on the TAD.
| |
| | | | |
| | ===OVERFLOW SIGNAL CACHING AND AGGREGATION (17710206)=== | | ===OVERFLOW SIGNAL CACHING AND AGGREGATION (17710206)=== |
| Line 273: |
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| | '''Inventor''' | | '''Inventor''' |
| | Bo LIU | | Bo LIU |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for caching signal requests. Signal requests are received by a signal processor from multiple computing devices. These requests are then sent to a signal data store. The signal processor monitors the rate at which the requests are received. If the rate exceeds a certain threshold set by the signal data store, any overflow requests are automatically redirected to an intermediate cache instead of the signal data store. The overflow requests in the intermediate cache are combined into one or more signal packages, each containing multiple overflow requests. These signal packages are then stored in the signal data store.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method for signal request caching is described. Signal requests are received at a signal processor from a plurality of computing devices. The received signal requests are routed to a signal data store. An ingestion rate of the received signal requests is monitored by the signal processor. When the ingestion rate meets a signal request rate threshold of the signal data store, overflow signal requests of the received signal requests are automatically routed to an intermediate cache instead of the signal data store. The overflow signal requests within the intermediate cache are aggregated into one or more signal packages, each of the one or more signal packages containing a plurality of overflow signal requests. The one or more signal packages are stored at the signal data store.
| |
| | | | |
| | ===Cache Data Provided Based on Data Availability (17707401)=== | | ===Cache Data Provided Based on Data Availability (17707401)=== |
| Line 284: |
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| | '''Inventor''' | | '''Inventor''' |
| | Ahmed ABDELSALAM | | Ahmed ABDELSALAM |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a computer method that involves a cache system. When a request for data is received, the cache checks if it already has the requested data. If the data is found in the cache, it is provided immediately. If the data is not found in the cache, a request is sent to the main memory to retrieve the data. At the same time, a flag is set to indicate that the request is pending. The cache then continues to process the next request for different data.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A computer implemented method includes receiving a first request at a cache for first data and checking the cache for the first data. In response to the first data residing in the cache, the first data is provided from the cache. In response to the first data not residing in the cache, a first memory request is sent to memory for the first data, a first request pending bit to is set indicate the first request is pending, and the cache proceeds to process a next request for second data.
| |
| | | | |
| | ===DESTINATION-AGNOSTIC ITEM-KEEPING UI FOR HETEROGENOUS DIGITAL ITEMS (17711844)=== | | ===DESTINATION-AGNOSTIC ITEM-KEEPING UI FOR HETEROGENOUS DIGITAL ITEMS (17711844)=== |
| Line 295: |
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| | '''Inventor''' | | '''Inventor''' |
| | Carlos German PEREZ | | Carlos German PEREZ |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The techniques described in this abstract allow systems to centralize access to digital items, regardless of where they are stored. Users can select items from their original location, such as a cloud storage platform, and store them in a centralized favorites section. This is done through an interface control, which can be accessed from any context or application. The system generates an alias for each selected item, which is then stored in the centralized location. Users can also move these aliases to different destinations, allowing for customized storage of items based on their type, origin, and location. The functionality of the interface control can be adjusted to accommodate the selected items.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The techniques disclosed herein enable systems to centralize access to various digital items irrespective of the location of those digital items. To achieve this, items that are stored at their original location, e.g., within a cloud storage platform, can be selected by a user for storage at a centralized location such as a favorites section. These items are selected using an interface control which can be an operating system component of an item keeping system that is accessible in any context or application. The item keeping system can generate an item alias for selected items which is then stored in the centralized location. In addition, item aliases can be moved to various destinations by the user to enable customized item storage for items of varying types, origin, and location. In addition, functionality of the interface control can be modified to suite selected items.
| |
| | | | |
| | ===DATA UNIFICATION (18331169)=== | | ===DATA UNIFICATION (18331169)=== |
| Line 306: |
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| | '''Inventor''' | | '''Inventor''' |
| | Meiyalagan BALASUBRAMANIAN | | Meiyalagan BALASUBRAMANIAN |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a solution for data unification, which involves receiving a data record with multiple data fields. A subset of these data fields is selected using a set of rules, and a stable identifier (stableID) is generated based on the content of this subset. The stableID is then inserted into a primary key data field of the data record.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Solutions for data unification include: receiving a data record, the data record comprising a plurality of data fields; selecting, from among the plurality of data fields, a subset of the data fields, the subset of the data fields being fewer in number than the plurality of data fields, wherein selecting the subset of the data fields comprises: applying a first rule to select at least a first one of the data fields within the data record for inclusion in the subset of the data fields; using content of the subset of the data fields, generating a stable identifier (stableID) for the data record; and inserting the stableID into a primary key data field of the data record.
| |
| | | | |
| | ===CONSTRAINT-BASED INDEX TUNING IN DATABASE MANAGEMENT SYSTEMS UTILIZING REINFORCEMENT LEARNING (17832274)=== | | ===CONSTRAINT-BASED INDEX TUNING IN DATABASE MANAGEMENT SYSTEMS UTILIZING REINFORCEMENT LEARNING (17832274)=== |
| Line 317: |
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| | '''Inventor''' | | '''Inventor''' |
| | Wentao WU | | Wentao WU |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system that uses reinforcement learning models to determine the best index configurations for processing workloads in a database management system. This system efficiently selects a subset of indexes that effectively utilize computing resources and minimize interference with customer workloads.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The present disclosure relates to systems, methods, and computer-readable media for determining optimal index configurations for processing workloads in a database management system. For instance, an index configuration system can efficiently determine a subset of indexes for processing a workload utilizing one or more reinforcement learning models. For example, in various implementations, the index configuration system utilizes a Markov decision process and/or a Monte Carlo tree search model to determine an optimal subset of indexes for processing a workload in a manner that effectively utilizes computing device resources while also avoiding significant interference with customer workloads.
| |
| | | | |
| | ===SNAPSHOT ISOLATION QUERY TRANSACTIONS IN DISTRIBUTED SYSTEMS (18328992)=== | | ===SNAPSHOT ISOLATION QUERY TRANSACTIONS IN DISTRIBUTED SYSTEMS (18328992)=== |
| Line 328: |
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| | '''Inventor''' | | '''Inventor''' |
| | Sarvesh SINGH | | Sarvesh SINGH |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes methods used in distributed systems to perform query transactions with snapshot isolation. These methods involve the use of systems and devices to execute queries in a distributed processing system. The system follows an isolation level protocol for managing data and data versioning across multiple data sets and compute pools within a logical server. A single transaction manager oversees the isolation semantics and data versioning.
| |
| − |
| |
| − | Read transactions are performed without locks, using the isolation semantics. The system also supports instant rollbacks, point-in-time queries, and single-phase commits. Abort and clean up operations are carried out based on a distributed abort protocol and the determination of the oldest active transaction in the system. The single transaction manager does not track read-only transactions, and client nodes do not maintain commit tables for transactions.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Methods for snapshot isolation query transactions in distributed systems are performed by systems and devices. Distributed executions of queries are performed in a processing system according to an isolation level protocol for data management and data versioning across one or more data sets, one or more compute pools, etc., within a logical server via a single transaction manager that oversees the isolation semantics and data versioning. Read transactions of queries are performed lock-free via the isolation semantics, and instant rollbacks, point-in-time queries, single-phase commits in the distributed systems are also provided. Abort and clean up operations are performed based on a distributed abort protocol and a determined oldest active transaction for the system in which the single transaction manager does not track read-only transactions, and client nodes do not maintain commit tables for transactions.
| |
| | | | |
| | ===FEDERATION OF DATA DURING QUERY TIME IN COMPUTING SYSTEMS (18206582)=== | | ===FEDERATION OF DATA DURING QUERY TIME IN COMPUTING SYSTEMS (18206582)=== |
| Line 341: |
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| | '''Inventor''' | | '''Inventor''' |
| | Helge Grenager Solheim | | Helge Grenager Solheim |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes techniques for federating data during query time. One example technique involves determining whether a file should be automatically replicated to a user shard in a different geographic region based on company policies or legal requirements. If replication is not permitted, the file is stored in a tenant shard in the original region, and a file reference is created in the user shard, pointing to the file stored in the tenant shard.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Techniques of federation of data during query time are disclosed herein. One example technique includes upon receiving an indication of interaction of a file by a user of a tenant, determining whether automatic replication of the file to a user shard corresponding to the user is permitted according to a company policy or a legal requirement, the user shard being in a second geographic region. The example technique can then include when automatic replication of the file is not permitted, storing the file in a tenant shard corresponding to the tenant in a network storage in the first geographic region and instead of replicating the file to the user shard in the second geographic region, creating, in the user shard in the second geographic region, a file reference that is a pointer to the file stored in the tenant shard in the network storage in the first geographic region.
| |
| | | | |
| | ===SYSTEM AND METHOD OF PROVIDING CONDITIONAL COPYING OF DATA (17711611)=== | | ===SYSTEM AND METHOD OF PROVIDING CONDITIONAL COPYING OF DATA (17711611)=== |
| Line 352: |
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| | '''Inventor''' | | '''Inventor''' |
| | Mukti Nikhil DESAI | | Mukti Nikhil DESAI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for copying a data object in a data environment to prevent copying failures. The method involves receiving a request to copy the data object to a destination source, which includes identifying two source data objects and indicating a preference for copying. The method then determines which source data object should be copied based on the preference. It examines a first source indicator to check if the first source data object is available for copying. If it is available, the data object is copied from the first source data object to the destination source. If it is not available, the data object is copied from the second source data object instead. Finally, the method creates an indication of successful copying to the destination source. Both source data objects are replicas of each other and contain the same data object.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method for performing conditional copying of a data object in a data environment to prevent a copying operation failure includes receiving a request to copy the data object to a destination source, the request including an identification of a first source data object, a second source data object and indication of an order of preference between the first data object and the second data object for copying the data object; determining based on the order that data object should be copied from the first source data object; examining a first source indicator to determine if the first source data object is available for copying; based on the determination, copying the data object from the first source data object to the destination source, when the first source data object is available and copying the copying the data object from the second source data object to the destination source, when the first source data object is not available; and creating an indication of successful copying of the data object to the destination source. The first source data object and the second source data object both contain the data object and the first source data object and the second source data object are active-active data objects that are replicas of each other.
| |
| | | | |
| | ===SYNCHRONOUS REPLICATION IN A DISTRIBUTED STORAGE ENVIRONMENT (18331404)=== | | ===SYNCHRONOUS REPLICATION IN A DISTRIBUTED STORAGE ENVIRONMENT (18331404)=== |
| Line 363: |
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| | '''Inventor''' | | '''Inventor''' |
| | Bradley Gene CALDER | | Bradley Gene CALDER |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a technology for synchronously replicating data in a distributed computing environment. It explains that there are two approaches to achieve this: eventual consistency and strong consistency. In the eventual consistency approach, data is written to a primary data store and then annotated with a record for replay at a secondary data store. Once the secondary data store acknowledges that it has written the data to a log, the primary data store commits the data and sends an acknowledgment of success to the client. In the strong consistency approach, the primary data store waits for an acknowledgment that the secondary data store has not only written but also committed the data before sending an acknowledgment of success to the client.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Embodiments of the present invention relate to synchronously replicating data in a distributed computing environment. To achieve synchronous replication both an eventual consistency approach and a strong consistency approach are contemplated. Received data may be written to a log of a primary data store for eventual committal. The data may then be annotated with a record, such as a unique identifier, which facilitates the replay of the data at a secondary data store. Upon receiving an acknowledgment that the secondary data store has written the data to a log, the primary data store may commit the data and communicate an acknowledgment of success back to the client. In a strong consistency approach, the primary data store may wait to send an acknowledgement of success to the client until it receives an acknowledgment that the secondary has not only written, but also committed, the data.
| |
| | | | |
| | ===WEB-SCALE PERSONALIZED VISUAL SEARCH RECOMMENDATION SERVICE (17710761)=== | | ===WEB-SCALE PERSONALIZED VISUAL SEARCH RECOMMENDATION SERVICE (17710761)=== |
| Line 374: |
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| | '''Inventor''' | | '''Inventor''' |
| | Li HUANG | | Li HUANG |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a system and method for returning personalized image-based search results. It explains that when a user submits a query with an image, the system generates a personalized item embedding based on the image and the user's profile information. It then obtains a set of candidate images based on this personalized item embedding. These candidate images are ranked according to the predicted level of user engagement and are diversified to ensure visual variety among the ranked images. Finally, a portion of these diversified images is returned as search results for the image-based query.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Systems and methods directed to returning personalized image-based search results are described. In examples, a query including an image may be received, and a personalized item embedding may be generated based on the image and user profile information associated with a user. Further, a plurality of candidate images may be obtained based on the personalized item embedding. The candidate images may then be ranked according to a predicted level of user engagement for a user, and then diversified to ensure visual diversity among the ranked images. A portion of the diversified images may then be returned in response to an image-based search.
| |
| | | | |
| | ===GUIDED SOURCE COLLECTION FOR A MACHINE LEARNING MODEL (17707026)=== | | ===GUIDED SOURCE COLLECTION FOR A MACHINE LEARNING MODEL (17707026)=== |
| Line 385: |
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| | '''Inventor''' | | '''Inventor''' |
| | Yu ZHANG | | Yu ZHANG |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for collecting data from a network graph and using it to train a machine learning model. The data is collected based on a domain-specific template that defines classifiers to guide the collection of relevant content. The method starts by analyzing a starting point in the graph and identifying relevant instances of the content. These instances are then added to a contextual protocol package. Each identified instance is further analyzed to find additional relevant content, which is also added to the package.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Data is collected from a network graph, wherein the collected data is useful for training a machine learning model on a query domain. A domain-specific template corresponding to the query domain is received, the domain-specific template defining one or more classifiers to guide collection of content relevant to the query domain from the network graph. A collection starting point is analyzed based on the one or more classifiers of the domain-specific template to identify one or more relevant instances of the content. The one or more identified relevant instances of the content are added to a contextual protocol package. Each identified relevant instance of the content is analyzed based on the one or more classifiers of the domain-specific template to identify one or more additional relevant instances of the content. The one or more identified additional relevant instances of the content are added to the contextual protocol package.
| |
| | | | |
| | ===BIAS REDUCING MACHINE LEARNING CORRECTION ENGINE FOR A MACHINE LEARNING SYSTEM (17708346)=== | | ===BIAS REDUCING MACHINE LEARNING CORRECTION ENGINE FOR A MACHINE LEARNING SYSTEM (17708346)=== |
| Line 396: |
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| | '''Inventor''' | | '''Inventor''' |
| | Xiaoyu CHAI | | Xiaoyu CHAI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes methods, systems, and computer-storage media for developing machine learning technology that is less prone to bias problems. It suggests using a loss adjustment weight to determine an adjusted loss function during model training, which helps reduce errors caused by sensitive features. The loss adjustment weight is determined based on the frequency of a feature-label combination of a sensitive feature. The adjusted loss function is then used to calculate loss during model training, resulting in an adjusted loss. The machine learning model is trained until the adjusted loss meets a predetermined threshold, indicating an acceptable level of model inaccuracy. These techniques aim to tailor machine learning systems to specific use cases and eliminate biases associated with certain data features.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Provided are methods, systems, and computer-storage media for developing machine learning technology that is less susceptible to bias problems. A machine learning model may be developed with reduced error attributed to one or more sensitive features by utilizing a loss adjustment weight to determine an adjusted loss function used to train the model. The loss adjustment weight may be determined based on a count of a feature-label combination of a sensitive feature. The adjusted loss function is determined and configured to use the loss adjustment weight when determining loss during model training, and the output of the adjusted loss function is an adjusted loss. The machine learning model may be trained until the adjusted loss satisfies a loss threshold, indicative of an acceptable level of model inaccuracy. Accordingly, present embodiments can provide use case specific tailoring to improve machine learning systems by removing biases associated with certain data features.
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| | | | |
| | ===DETECTING ANOMALOUS POST-AUTHENTICATION BEHAVIOR FOR A WORKLOAD IDENTITY (17708855)=== | | ===DETECTING ANOMALOUS POST-AUTHENTICATION BEHAVIOR FOR A WORKLOAD IDENTITY (17708855)=== |
| Line 407: |
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| | '''Inventor''' | | '''Inventor''' |
| | Shinesa Elaine CAMBRIC | | Shinesa Elaine CAMBRIC |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for detecting unusual behavior or changes in the state of a workload identity after authentication. It involves analyzing audit logs that record actions taken with respect to the workload identity. These logs are analyzed using a model that predicts anomalies based on the actions recorded. The model generates a score indicating the likelihood that a particular sequence of actions represents anomalous behavior or state changes. If an anomaly is detected, a mitigation action is taken to address the issue.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to detect anomalous post-authentication behavior/state change(s) with respect to a workload identity. For example, audit logs that specify actions performed with respect to the workload identity of a platform-based identity service, a causing state change(s), while another identity is authenticated with the platform-based identity service, are analyzed. The audit log(s) are analyzed via a model for anomaly prediction based on actions. The model generates an anomaly score indicating a probability whether a particular sequence of the actions is indicative of anomalous behavior/state change(s). A determination is made that an anomalous behavior has occurred based on the anomaly score, and when anomalous behavior has occurred, a mitigation action may be performed that mitigates the anomalous behavior.
| |
| | | | |
| | ===PRIVATE PRESENTATION OF SENSITIVE CONTENT (17657903)=== | | ===PRIVATE PRESENTATION OF SENSITIVE CONTENT (17657903)=== |
| Line 418: |
Line 212: |
| | '''Inventor''' | | '''Inventor''' |
| | Eli REVACH | | Eli REVACH |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a technology that allows for the safe access of sensitive content in potentially unsafe environments. It explains that a host computing device can receive a request to display a content item, check the security information associated with the content, and determine the current environment of the device. If the content is deemed sensitive and the environment is considered unsafe, the device will prevent the content from being displayed on its own output device and instead send it to a private presentation device.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Examples are disclosed that relate to safely accessing sensitive content in non-safe environments. One example provides a host computing device comprising an output device, a processor, and memory comprising instructions executable by the processor. The instructions are executable to receive a request to present a content item, access security information for the content item, and determine a current environment of the host computing device. The instructions are further executable to, when it is determined from the security information that the content item is a sensitive content item and that the current environment is not a safe environment for the content item, prevent presentation of the content item by the output device and send the content item to a private presentation device.
| |
| | | | |
| | ===DOCUMENT CONVERSION ENGINE (18011792)=== | | ===DOCUMENT CONVERSION ENGINE (18011792)=== |
| Line 429: |
Line 217: |
| | '''Inventor''' | | '''Inventor''' |
| | Tomasz L. Religa | | Tomasz L. Religa |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a system and method for converting a document into a presentation. The system identifies sections in the document and creates section titles and summaries for each section. It then transforms the document into slides, with each slide corresponding to a section and including the section title and summary. Finally, the system generates a presentation document based on these slides.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A system and method for converting a document is described. The system accesses a document comprising one or more section breaks. The system detects sections of the text document demarked by the one or more section breaks and generates a section title metadata and a section summary metadata for each section of the plurality of sections. The system inserts the section title metadata and the section summary metadata at the corresponding section breaks in the text document. The system modifies the text document into slides. Each slide being formed for each section based on the corresponding section title metadata and the section summary metadata. The system generates a presentation document based on the slides.
| |
| | | | |
| | ===SPARSITY AND QUANTIZATION FOR DEEP NEURAL NETWORKS (17664616)=== | | ===SPARSITY AND QUANTIZATION FOR DEEP NEURAL NETWORKS (17664616)=== |
| Line 440: |
Line 222: |
| | '''Inventor''' | | '''Inventor''' |
| | Rasoul SHAFIPOUR | | Rasoul SHAFIPOUR |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a computing system that uses a deep neural network to process inputs and generate outputs. The network consists of an input layer, hidden layers, and an output layer. The system includes nodes that operate on the inputs to produce inferences, and these nodes are controlled by parameters of the network. The system also has a sparsity controller that can adjust the parameter density of the network by applying different levels of sparsity. Additionally, there is a quantization controller that can quantize the parameters of the network based on the sparsity level, meaning the quantization applied to each parameter depends on the specific sparsity state it falls under.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A computing system is configured to implement a deep neural network comprising an input layer for receiving inputs applied to the deep neural network, an output layer for outputting inferences based on the received inputs, and a plurality of hidden layers interposed between the input layer and the output layer. A plurality of nodes selectively operate on the inputs to generate and cause outputting of the inferences, wherein operation of the nodes is controlled based on parameters of the deep neural network. A sparsity controller is configured to selectively apply a plurality of different sparsity states to control parameter density of the deep neural network. A quantization controller is configured to selectively quantize the parameters of the deep neural network in a manner that is sparsity-dependent, such that quantization applied to each parameter is based on which of the plurality of different sparsity states applies to the parameter.
| |
| | | | |
| | ===MIXTURE OF EXPERTS MODELS WITH SPARSIFIED WEIGHTS (17657604)=== | | ===MIXTURE OF EXPERTS MODELS WITH SPARSIFIED WEIGHTS (17657604)=== |
| Line 451: |
Line 227: |
| | '''Inventor''' | | '''Inventor''' |
| | Bita DARVISH ROUHANI | | Bita DARVISH ROUHANI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for operating a machine learning model that includes multiple layers of neural networks called "mixture of experts layers." The method involves receiving input data and sending it to a routing gate network. This network determines which neural network expert in the mixture of experts layer should evaluate each input data shard. A weight matrix is then retrieved for each designated expert, which has a predetermined sparsity (meaning it contains mostly zeros). This sparsified expert is used to evaluate the input data shard. Overall, this method allows for efficient evaluation of input data using a mixture of experts model.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method is presented for operating a machine learning model including one or more mixture of experts layers. The method comprises receiving one or more input data shards at a routing gate network for a mixture of experts layer comprising a plurality of neural network experts. One or more neural network experts in the mixture of experts layer is designated layer to evaluate each input data shard. For each designated neural network expert, a weight matrix is retrieved having a predetermined sparsity to generate a sparsified designated neural network expert. Each input data shard is evaluated with a respective sparsified designated neural network expert.
| |
| | | | |
| | ===MACHINE LEARNING MODEL PROCESSING BASED ON PERPLEXITY (17657606)=== | | ===MACHINE LEARNING MODEL PROCESSING BASED ON PERPLEXITY (17657606)=== |
| Line 462: |
Line 232: |
| | '''Inventor''' | | '''Inventor''' |
| | Bita DARVISH ROUHANI | | Bita DARVISH ROUHANI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for operating a machine learning model that uses sequential transformer blocks. The method involves receiving input data and processing it using a mixture of experts layer. An auxiliary classifier determines the perplexity (a measure of uncertainty) of the processed data. Based on this perplexity measure, one or more experts in a downstream transformer block are identified to process the input data further. Weight matrices are then fetched for these identified experts.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method for operating a machine learning model is presented. The machine learning model includes a plurality of sequential transformer blocks. The method comprises receiving input data at a transformer block and processing the input data via a mixture of experts layer. At an auxiliary classifier, a measure of perplexity of the processed input data is determined. Based on the determined measure of perplexity, one or more experts in a downstream transformer block that will subsequently process the input data are indicated. Weight matrices are then fetched for the indicated one or more experts.
| |
| | | | |
| | ===DRIFT DETECTION USING AN AUTOENCODER WITH WEIGHTED LOSS (17731908)=== | | ===DRIFT DETECTION USING AN AUTOENCODER WITH WEIGHTED LOSS (17731908)=== |
| Line 473: |
Line 237: |
| | '''Inventor''' | | '''Inventor''' |
| | Kiran RAMA | | Kiran RAMA |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a technique for detecting data drift using artificial neural networks (ANN). The technique involves determining the importance of different features in a machine learning (ML) model. An autoencoder is used to learn encodings of the features and regenerate them based on these encodings. The loss function of the autoencoder is weighted by the feature importance values. A reconstruction error, calculated based on the weighted loss, is compared to a threshold. If the reconstruction error exceeds the threshold, it indicates that the data has drifted. In response to this detection, appropriate actions are taken to mitigate the data drift in the ML model.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Embodiments described herein are directed to ANN-based drift detection techniques for detecting data drift. For example, feature importance values of features provided to an ML model are determined. An input feature vector comprising a plurality of feature values are provided as an input to an autoencoder, which is configured to learn encodings representative of the features provided thereto and regenerate the features based on the encodings. The loss function (or re-construction loss) of the autoencoder is weighted by the feature importance values. A re-construction error based on the weighted loss is determined. The re-construction error is compared to a threshold condition. In response to determining that the re-construction error meets the threshold condition, a determination is made that the data has drifted. Responsive to determining that data has drifted, an action is taken with respect to the ML model to mitigate the data drift.
| |
| | | | |
| | ===Analog Multiply-and-Accumulate Circuit Aware Training (17709976)=== | | ===Analog Multiply-and-Accumulate Circuit Aware Training (17709976)=== |
| Line 484: |
Line 242: |
| | '''Inventor''' | | '''Inventor''' |
| | Yehonathan REFAEL KALIM | | Yehonathan REFAEL KALIM |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes techniques for training neural networks (NN) in order to reduce power consumption and inference time. During training, an estimate of the power consumed by the hardware accelerator on which the NN runs is determined. This estimate is based on the non-zero midterms generated by the accelerator and their precision. The loss function of the NN is modified to incorporate the non-zero midterms and their precision. This modified loss function encourages the generation of a sparse bit representation of the NN's weights and reduces the precision of the accelerator. Additionally, noise can be injected at the output of the NN's nodes to simulate the noise experienced by the accelerator during inference. This allows the weights to account for the intrinsic noise of the accelerator.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Embodiments described herein are directed to training techniques to reduce the power consumption and decrease the inference time of an NN. For example, during training, an estimate of power consumed by AMACs of a hardware accelerator on which the NN executes during inferencing is determined. The estimate is based at least on the non-zero midterms generated by the AMACs and the precision thereof. A loss function of the NN is modified such that it formulates the non-zero midterms and the precision thereof. The training forces the modified loss function to generate a sparse bit representation of the weights of the NN and to reduce the precision of the AMACs. Noise may also be injected at the output of nodes of the NN that emulates noise generated at an output of the AMACs. This enables the weights to account for the intrinsic noise that is experienced by the AMACs during inference.
| |
| | | | |
| | ===SPARSITY MASKING METHODS FOR NEURAL NETWORK TRAINING (17657112)=== | | ===SPARSITY MASKING METHODS FOR NEURAL NETWORK TRAINING (17657112)=== |
| Line 495: |
Line 247: |
| | '''Inventor''' | | '''Inventor''' |
| | Maximilian Taylor GOLUB | | Maximilian Taylor GOLUB |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for training a neural network. It involves using a weight matrix with integer dimensions. First, a balanced sparsity mask is created for the weight matrix in the first dimension. This mask is applied during the inference process. Then, a second balanced sparsity mask is generated for the transpose of the weight matrix in the second dimension. This mask is applied during the backpropagation process. Overall, this method aims to improve the training efficiency of the neural network.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method is presented for training a neural network. For a weight matrix having integer dimensions Min a first dimension and an integer dimension Min a second dimension, a first balanced sparsity mask is generated that is an Nof Mmask in the first dimension. The first balanced sparsity mask is applied to the weight matrix during inference. A second balanced sparsity mask is generated for a transpose of the weight matrix. The second balanced sparsity mask is an Nof Mmask in the second dimension. The second balanced sparsity mask is applied to the transpose of the weight matrix during backpropagation.
| |
| | | | |
| | ===CONTEXTUAL DATA ANALYSIS IN COMPUTING SYSTEMS (17708157)=== | | ===CONTEXTUAL DATA ANALYSIS IN COMPUTING SYSTEMS (17708157)=== |
| Line 506: |
Line 252: |
| | '''Inventor''' | | '''Inventor''' |
| | Ananthatejas Raghavan | | Ananthatejas Raghavan |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes techniques for analyzing contextual data in distributed computing systems. It explains that operational data and attribute data representing the attributes of multiple entities in the system are received. Using machine learning, a decision tree is generated based on this data. The decision tree consists of a root and multiple branches, each representing a set of attributes and a probability value indicating the likelihood of an event occurring in the system associated with one of the components with those attributes. The branches can be parsed to identify a common subset of attributes that are most closely related to the occurrence of the event in the system.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Techniques of contextual data analysis in distributed computing systems are disclosed herein. In one example, upon receiving operational data and attribute data representing attributes of multiple entities in the distributed computing system, a decision tree is generated based on the received operational and attribute data via machine learning. The decision tree has a root and multiple branches each representing a set of the attributes in the attribute data and a corresponding probability value representing a likelihood that one of the multiple components with the set of the attributes would be associated with an event in the distributed computing system. The multiple branches can then be parsed to identify a common subset of the attributes of the multiple components as most closely related to an occurrence of the event in the distributed computing system.
| |
| | | | |
| | ===SYSTEM AND METHOD FOR IDENTIFYING AND RESOLVING PERFORMANCE ISSUES OF AUTOMATED COMPONENTS (17706712)=== | | ===SYSTEM AND METHOD FOR IDENTIFYING AND RESOLVING PERFORMANCE ISSUES OF AUTOMATED COMPONENTS (17706712)=== |
| Line 517: |
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| | '''Inventor''' | | '''Inventor''' |
| | Yasmin BOKOBZA | | Yasmin BOKOBZA |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system and method for identifying and resolving performance issues in automated components. These components are divided into groups using a clustering algorithm, and initial centroids for the algorithm are selected based on context rules. Each group is then ranked based on performance features and their importance, which is determined by training a machine learning model. This model classifies the components into groups based on their performance features and the groups they were assigned to.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Systems and methods are described for identifying and resolving performance issues of automated components. The automated components are segmented into groups by applying a K-means clustering algorithm thereto based on segmentation feature values respectively associated therewith, wherein an initial set of centroids for the K-means clustering algorithm is selected by applying a set of context rules to the automated components. Then, for each group, a performance ranking is generated based at least on a set of performance feature values associated with each of the automated components in the group and a feature importance value for each of the performance features. The feature importance values are determined by training a machine learning based classification model to classify automated components into each of the groups, wherein the training is performed based on the respective performance feature values of the automated components and the respective groups to which they were assigned.
| |
| | | | |
| | ===AUTO-MANAGING REQUESTOR COMMUNICATIONS TO ACCOMMODATE PENDING ACTIVITIES OF DIVERSE ACTORS (17710626)=== | | ===AUTO-MANAGING REQUESTOR COMMUNICATIONS TO ACCOMMODATE PENDING ACTIVITIES OF DIVERSE ACTORS (17710626)=== |
| Line 528: |
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| | '''Inventor''' | | '''Inventor''' |
| | Ryen W. WHITE | | Ryen W. WHITE |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The present disclosure describes a system that helps a requester manage activities across different individuals or groups. The system receives a task request from the requester and also collects information about the individuals or groups involved. Based on this information, the system assigns the task to a specific individual or group and sends them a message requesting them to complete the task.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Aspects of the present disclosure relate to assisting a requestor to manage activities a cross a plurality of diverse actors. In examples, a system is provided that includes at least one processor, and memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations. The set of operations include receiving a request for a task to be completed, from the requestor, receiving actor context data, recording an assignment of the task to an actor, based on the actor context data, generating a communication to request that the actor complete the assigned task, and sending the communication to the actor.
| |
| | | | |
| | ===NESTED MODEL STRUCTURES FOR THE PERFORMANCE OF COMPLEX TASKS (17709157)=== | | ===NESTED MODEL STRUCTURES FOR THE PERFORMANCE OF COMPLEX TASKS (17709157)=== |
| Line 539: |
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| | '''Inventor''' | | '''Inventor''' |
| | Mohit SEWAK | | Mohit SEWAK |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system that uses nested model structures to ensure compliance with policies within a computer system. It involves analyzing digital records using multiple models arranged in a hierarchical structure. Each model analyzes a part of the record, and their combined analysis determines if the content violates a system policy. If a violation is detected, mitigation actions are taken, which may change how the record is transmitted in the future.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The disclosure is directed to systems, methods, and computer storage media, for, among other things, employing nested model structures to enforce compliance, within a computational system, to at least one policy. One method includes receiving a digital record that encodes content. A plurality of models (e.g., integrated models and/or model droplets) is employed to analyze the records. The plurality of models is configured and arranged within a nested structure of a hierarchy of models. Each of the plurality of models analyzes at least a portion of the record. Based on the nested structure, the hierarchy combines the analysis from each of the plurality of models to determine that the content violates a policy of a system. In response to determining that the content violates the policy, at least one mitigation (or intervention) action are performed. The at least one mitigation action may alter subsequent transmissions of the record.
| |
| | | | |
| | ===METHOD AND SYSTEM OF INTELLIGENTLY MANAGING CUSTOMER SUPPORT REQUESTS (17712678)=== | | ===METHOD AND SYSTEM OF INTELLIGENTLY MANAGING CUSTOMER SUPPORT REQUESTS (17712678)=== |
| Line 550: |
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| | '''Inventor''' | | '''Inventor''' |
| | Sunil SINGHAL | | Sunil SINGHAL |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a system and method for automatically identifying the appropriate operating procedure to resolve a customer support request. The system receives a customer support request and encodes the issue into text representations. These representations are then compared to a database of operating procedure encodings using a matching and selection unit. The system identifies one or more operating procedures that can resolve the issue and provides them as recommendations. The text representations and operating procedure encodings are generated using a geometric progressing natural language processing algorithm.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A system and method for automatically identifying an operating procedure for resolving a customer support request includes receiving a customer support request for resolving an issue, encoding the issue into one or more text encoding representations, providing the one or more text encoding representations as a first input to a matching and selection unit, providing operating procedure encodings for a plurality of operating procedures as a second input to the matching and selection unit, comparing, by the matching and selection unit, the one or more text encoding representations to the operating procedure encodings to identify one or more operating procedures for resolving the issue, and providing the one or more operating procedures as recommendations for resolving the issue, wherein at least one of the one or more text encoding representations and the operating procedure encodings are generated by utilizing a geometric progressing natural language processing (NLP) algorithm.
| |
| | | | |
| | ===SYSTEM AND METHOD FOR GENERATING PERSONALIZED EFFICIENCY RECOMMENDATIONS (17656915)=== | | ===SYSTEM AND METHOD FOR GENERATING PERSONALIZED EFFICIENCY RECOMMENDATIONS (17656915)=== |
| Line 561: |
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| | '''Inventor''' | | '''Inventor''' |
| | Ritesh KINI | | Ritesh KINI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system that receives personalization profile parameters from a user of a relevant resource device. It then calculates a representative utilization of the device based on these parameters and generates a recommendation based on this utilization and the personalization profile parameters.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A system includes: a processor; and memory including instructions that, when executed by the processor, cause the processor to: receive personalization profile parameters from a user of a relevant resource device; calculate a representative utilization of the relevant resource device based on the personalization profile parameters; and generate the recommendation based on the representative utilization and the personalization profile parameters.
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| | | | |
| | ===REPAIRING IMAGE DEPTH VALUES FOR AN OBJECT WITH A LIGHT ABSORBING SURFACE (17713038)=== | | ===REPAIRING IMAGE DEPTH VALUES FOR AN OBJECT WITH A LIGHT ABSORBING SURFACE (17713038)=== |
| Line 572: |
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| | '''Inventor''' | | '''Inventor''' |
| | JingJing SHEN | | JingJing SHEN |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a system that can detect and track the position of an object (such as a head-mounted display) in a color image using a 3D model of the object. The system can then fix depth values associated with a specific part of the object that absorbs light from a depth sensor, resulting in a color-depth image that does not have dark areas around that part of the object.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The techniques described herein disclose a system that is configured to detect and track the three-dimensional pose of an object (e.g., a head-mounted display device) in a color image using an accessible three-dimensional model of the object. The system uses the three-dimensional pose of the object to repair pixel depth values associated with a region (e.g., a surface) of the object that is composed of material that absorbs light emitted by a time-of-flight depth sensor to determine depth. Consequently, a color-depth image (e.g., a Red-Green-Blue-Depth image or RGB-D image) can be produced that does not include dark holes on and around the region of the object that is composed of material that absorbs light emitted by the time-of-flight depth sensor.
| |
| | | | |
| | ===REUSE OF INFOGRAPHICS (18020360)=== | | ===REUSE OF INFOGRAPHICS (18020360)=== |
| Line 583: |
Line 287: |
| | '''Inventor''' | | '''Inventor''' |
| | Weiwei CUI | | Weiwei CUI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a solution for reusing infographics. It involves determining a group of visual elements from an original infographic, where each visual element represents an information item. Correlations between the visual elements and the information items, as well as between the visual elements within the group, are determined. A description of the original infographic is generated based on these correlations. A target infographic is then created by updating the group of visual elements using the description and target information. This solution simplifies the reuse of infographics and improves user experience.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | In accordance with the implementations of the subject matter described herein, there is provided a solution for reusing infographics. In this solution, a group of visual element units is determined from a visual element set comprised in the original infographic. A visual element unit in the group represents an information item in the original infographic. A first correlation between a visual element contained in the visual element unit and the information item and a second correlation between the visual element unit and a further visual element unit in the group are determined. A description for the original infographic is generated based on the first and second correlations. A target infographic is generated by updating the group of visual element units at least based on the description and the target information. In this way, infographics can be converted into reusable templates, thereby simplifying reuse of such infographics and improving user experience.
| |
| | | | |
| | ===MESH SIMPLIFICATION (17657736)=== | | ===MESH SIMPLIFICATION (17657736)=== |
| Line 594: |
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| | '''Inventor''' | | '''Inventor''' |
| | Deboshmita GHOSH | | Deboshmita GHOSH |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for identifying and analyzing the hand in a 3D mesh model. The initial mesh is processed to create a smoother version, and the curvature of each vertex is calculated. Based on a certain threshold, potential finger vertices are identified. From these potential vertices, seed vertices are selected based on the curvature of their neighboring vertices. These seed vertices are then expanded to create patches representing different parts of the hand. Finally, these patches are deprioritized for simplification of the mesh model.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | An initial mesh is received comprising a hand of a subject. The initial mesh includes a plurality of vertices. A smoothed mesh is generated, and a discrete curvature of the smoothed mesh is determined for each vertex. One or more candidate finger vertices are identified based upon a determination that the discrete curvature for each of the one or more candidate vertices is greater than or equal to a threshold curvature. One or more seed vertices are identified from among the one or more candidate finger vertices based upon a determination that the discrete curvature for one or more other vertices within a neighborhood of each seed vertex is greater than or equal to the threshold curvature. Dilation is performed on the one or more seed vertices to grow one or more patches from the one or more seed vertices. The one or more patches are deprioritized for mesh simplification.
| |
| | | | |
| | ===SALIENCY-BASED DIGITAL ENVIRONMENT ADAPTATION (17710652)=== | | ===SALIENCY-BASED DIGITAL ENVIRONMENT ADAPTATION (17710652)=== |
| Line 605: |
Line 297: |
| | '''Inventor''' | | '''Inventor''' |
| | Elnaz NOURI | | Elnaz NOURI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for determining the importance or relevance of content and locations in a digital environment. This is done by assigning a saliency metric to each instance of content or location. These metrics are then used to rank and prioritize the content and locations. The digital environment can be adapted based on this ranking, such as by presenting certain assets to the user or altering game mechanics. Additionally, content from other digital environments can be incorporated into the adaptation process. Overall, the saliency metric is used to evaluate and adapt different aspects of the digital environment.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | In examples, a saliency metric may be determined for an instance of content and/or a location of a digital environment. Accordingly, a set of candidate content and/or locations may be ranked according to associated saliency metrics, such that content and/or an associated location with which to adapt the digital environment for a given user may be determined from a set of candidates. For example, the digital environment may be adapted to present a two-dimensional or a three-dimensional asset to a user. As another example, a game mechanic of the digital environment may be altered. In examples, content from another digital environment may be identified and used to adapt the digital environment, thereby incorporating external content. Thus, a saliency metric associated with a location or an instance of content may be used to programmatically generate a relative or absolute metric with which to evaluate and adapt aspects of the digital environment.
| |
| | | | |
| | ===ATMOSPHERIC CHEMICAL SPECIES DETECTION USING MULTISPECTRAL IMAGING (17804815)=== | | ===ATMOSPHERIC CHEMICAL SPECIES DETECTION USING MULTISPECTRAL IMAGING (17804815)=== |
| Line 616: |
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| | '''Inventor''' | | '''Inventor''' |
| | Sara MALVAR MAUA | | Sara MALVAR MAUA |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for using optical techniques to detect a specific chemical species in the atmosphere. Multispectral imagery of a geographic region is captured, which includes different bands of light. One of these bands is more sensitive to the target chemical species than the others. A background reflectance map is created by combining the intensity values of the other bands. The intensity values of the target band are then compared to the background reflectance map to determine the presence and intensity of the target chemical species.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Techniques for optically detecting a subject chemical species within an atmospheric environment are disclosed. Image data is obtained representing multispectral imagery of a geographic region captured through the atmospheric environment. The image data includes an array of band-specific intensity values for each of a plurality of spectral bands, including a sample spectral band having increased sensitivity to the subject chemical species as compared to a plurality of reference spectral bands. A background reflectance map is generated that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of albedo-normalized arrays for a grouped subset of the plurality of reference spectral bands. The albedo-normalized array of band-specific intensity values for the sample spectral band is compared to the background reflectance map to obtain an index array of intensity variance values for the subject chemical species.
| |
| | | | |
| | ===TEXTLESS MATERIAL SCENE MATCHING IN VIDEOS (17804188)=== | | ===TEXTLESS MATERIAL SCENE MATCHING IN VIDEOS (17804188)=== |
| Line 627: |
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| | '''Inventor''' | | '''Inventor''' |
| | Mattan SERRY | | Mattan SERRY |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a system and method for matching video shots that contain text with corresponding shots that do not have text. The system divides the video into shots and identifies shots with similar durations. It then compares the image content in representative frames of these shots to determine if they match. If a match is found, the system pairs the shots, where one sequence contains shots with text and the other sequence contains the same shots without text. The system may also replace the shots with text in the second sequence.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Systems, methods, and a computer-readable medium are provided for matching textless elements to texted elements in video content. A video processing system including a textless matching system may divide a video into shots, identify shots having similar durations, identify sequences of shots having similar durations, and compare image content in representative frames of the sequences to determine whether the sequences match. When the sequences are determined to match, the sequences may be paired, wherein the first sequence may include shots with overlaid text and the second sequence may include textless version of corresponding texted shots included in the first sequence. In some examples, the video processing system may further replace the determined corresponding texted shots.
| |
| | | | |
| | ===ASSIGNING SSML TAGS TO AN AUDIO CORPUS (17710733)=== | | ===ASSIGNING SSML TAGS TO AN AUDIO CORPUS (17710733)=== |
| Line 638: |
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| | '''Inventor''' | | '''Inventor''' |
| | Mikayel MIRZOYAN | | Mikayel MIRZOYAN |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This system converts audio objects such as audio books, podcasts, and videoconference meetings into text with SSML tags. These tags enhance the speech synthesis process to make it sound more human-like. The system analyzes the audio to identify different speech characteristics for each token. These characteristics can differentiate between different characters speaking. The system assigns tokens to characters and compares the speech characteristics of each token to a baseline characteristic associated with a specific character. By measuring the deviation between the token's speech characteristic and the baseline, the system determines a relative speech output characteristic value. This value is then included in an SSML tag for that token.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | This disclosure describes a system that converts an audio object (e.g., an audio book, a podcast, a videoconference meeting) to text with SSML tags so that any future text-to-speech conversion enables speech synthesis to sound more human-like. The system analyzes the audio object to identify speech output characteristics for different tokens. Variations in speech output characteristics can distinguish between an utterance spoken by one character and an utterance spoken by another character. The system assigns the tokens to the characters and compares a speech output characteristic for a token to a baseline speech output characteristic associated with an identified character. Next, the system determines an amount of deviation between the speech output characteristic for the token and the baseline speech output characteristic. The system uses this deviation to determine a relative speech output characteristic value, which is to be included in an SSML tag for a token.
| |
| | | | |
| | ===EFFICIENCY ADJUSTABLE SPEECH RECOGNITION SYSTEM (18331742)=== | | ===EFFICIENCY ADJUSTABLE SPEECH RECOGNITION SYSTEM (18331742)=== |
| Line 649: |
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| | '''Inventor''' | | '''Inventor''' |
| | Yu WU | | Yu WU |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a computing system that trains a speech recognition model using a deep neural network. The model consists of two parts: a transformer encoder network and a transducer predictor network. The model is designed to have adjustable hyperparameters that can be dynamically configured to optimize its efficiency or performance when deployed on a device. This is done by considering the computational power of the device and adjusting the hyperparameters accordingly.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The computing system trains an end-to-end (E2E) automatic speech recognition (ASR) model, using a transformer-transducer-based deep neural network that comprises a transformer encoder network and a transducer predictor network. The E2E ASR model is trained to have one or more adjustable hyperparameters that are configured to dynamically adjust an efficiency or a performance of the E2E ASR model when the E2E ASR model is deployed onto a device or executed by the device, by identifying one or more conditions of the device associated with computational power of the device and setting at least one of the one or more adjustable hyperparameters based on one or more conditions of the device.
| |
| | | | |
| | ===MAGNETICALLY PRELOADED PUSH BUTTON (17711186)=== | | ===MAGNETICALLY PRELOADED PUSH BUTTON (17711186)=== |
| Line 660: |
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| | '''Inventor''' | | '''Inventor''' |
| | Michael Cameron GORDON | | Michael Cameron GORDON |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract discusses the use of dome switches in push buttons and the challenges associated with achieving consistent tactile feedback. Traditional methods of preloading the dome switch to close any gaps in the push button design can be expensive and difficult to reproduce consistently during manufacturing. However, a new pre-load design has been developed that does not require pre-depression of the dome switch, allowing for greater tolerance to manufacturing variations.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Push buttons utilizing dome switches are often preloaded to take up any tolerances in the push button design causing a gap and provide consistent tactile feedback to a user. However, conventional push button preload techniques can be costly and difficult to consistently reproduce during push button manufacturing. A new pre-load design does not require pre-depression of the dome switch to close the gap, which permits a more forgiving tolerance to manufacturing variations.
| |
| | | | |
| | ===METHOD AND APPARATUS FOR COMPRESSION MULTIPLEXING FOR SPARSE COMPUTATIONS (17687559)=== | | ===METHOD AND APPARATUS FOR COMPRESSION MULTIPLEXING FOR SPARSE COMPUTATIONS (17687559)=== |
| Line 671: |
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| | '''Inventor''' | | '''Inventor''' |
| | Ankit MORE | | Ankit MORE |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The present disclosure describes a digital circuit and method for compressing input digital values. The circuit receives a set of input digital values, which can be either zero or non-zero values. These values are then processed through a series of switching stages. In the first switching stage, the non-zero values are rearranged and compressed, while the zero values are ignored. The compressed non-zero values are then shifted and sent to the inputs of a second switching stage. In the second switching stage, the non-zero values are consecutively connected to a smaller number of outputs compared to the number of inputs in the first stage. This compression and shift process allows for the efficient compression of input digital values.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Embodiments of the present disclosure include a digital circuit and method for compressing input digital values. A plurality of input digital values may include zero values and non-zero values. The input digital values are received on M inputs of a first switching stage. The first switching stage is arranged in groups that rearrange the non-zero values on first switching stage outputs according to a compression and shift. The compression and shift position the non-zero values on outputs coupled to inputs of a second switching stage. The second switching stage consecutively couples non-zero values to N outputs, where N is less than M.
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| | | | |
| | ===LOW-CODE/NO-CODE MACHINE LEARNING DATA STREAM ANALYSIS SYSTEM (17710302)=== | | ===LOW-CODE/NO-CODE MACHINE LEARNING DATA STREAM ANALYSIS SYSTEM (17710302)=== |
| Line 682: |
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| | '''Inventor''' | | '''Inventor''' |
| | Karl DAVIES-BARRETT | | Karl DAVIES-BARRETT |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system that uses a low-code or no-code approach to develop and deploy machine learning analysis systems. The system includes a cloud service that receives data from a sensor device and trains a machine-learning model to recognize specific elements in the data. The trained model is then deployed to an edge datacenter, which receives a second data stream and uses the model to identify the selected elements in the data. A logic service allows users to define logical rules based on the identified elements. These logical rules are then applied to the element set.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The present application relates to developing and deploying machine learning analysis systems using a low-code or no-code approach. A cloud service is configured to receive a first data stream from a sensor device and train a machine-learning model to recognize selected elements of the first data stream that are selected from a package of template models via a graphical user interface. The cloud service deploys the machine-learning model to an edge datacenter configured to receive a second data stream via a network connection. The edge datacenter locally interrogates the second data stream based on the machine-learning model to generate an element set including the selected elements. A logic service may receive a selection of one or more properties of the element set and one or more logical operators via a graphical user interface to generate user-configured logical rules. The logic service may the user-configured logical rules to the element set.
| |
| | | | |
| | ===USING A ROUTING PROTOCOL FOR NETWORK PORT FAILOVER (17712913)=== | | ===USING A ROUTING PROTOCOL FOR NETWORK PORT FAILOVER (17712913)=== |
| Line 693: |
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| | '''Inventor''' | | '''Inventor''' |
| | Kenyon James HENSLER | | Kenyon James HENSLER |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method for network port failover using a routing protocol. It explains that a network stack, which is a set of software components that handle network communication, has a loopback interface with a specific IP address, as well as two other interfaces connected to different network ports. The routing protocol is set up to communicate with remote network devices through these interfaces. Initially, the default route of the network stack is configured to send IP packets through the second interface. However, if there is a failure with this interface, the routing protocol will indicate the issue and the default route will be changed to send IP packets through the third interface instead.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Using a routing protocol for network port failover. A network stack, which does not perform reverse path forwarding, includes a first interface as a loopback interface that is assigned a first internet protocol (IP) address, a second interface to a first network port, and a third interface to a second network port. The routing protocol is configured to communicate over the second interface with a first port at remote network device(s), and to communicate over the third interface with a second port at the remote network device(s). A route comprising the first IP address is announced to the remote network device(s), and default route of the network stack is configured to egress IP packets via the second interface. Later, the routing protocol indicates that there is a forwarding failure associated with the second interface, and the default route is configured to egress IP packets via the third interface.
| |
| | | | |
| | ===DYNAMIC CLOUD OFFLOADING (17708074)=== | | ===DYNAMIC CLOUD OFFLOADING (17708074)=== |
| Line 704: |
Line 342: |
| | '''Inventor''' | | '''Inventor''' |
| | Sagiv DRAZNIN | | Sagiv DRAZNIN |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a system that automatically offloads applications from an on-premises server to a cloud service provider when there is a spike in resource demand. The system monitors the resource demand of applications and creates a cloud instance to handle the increased demand. The cloud space is preconfigured for specific types of processing, such as mobile traffic or websites/databases, and may include resource requirements, time constraints, provisioning, and testing/validation.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A dynamic offloading system is provided, which monitors resource demand by one or more applications executing on an on-prem server and supply of curated cloud space on one or more registered cloud service providers to automatically create an instance and offload applications associated with spikes in the resource demand. The curated cloud space may be preconfigured for specific processing and/or more general processing. For instance, the curated cloud space may be preconfigured for offloading service applications associated with mobile traffic, which may include specific resource requirements, time or service constraints, provisioning, testing or validation. Additionally, the curated cloud space may be preconfigured for offloading websites or databases, which may have more generalized resource requirements, provisioning, testing or validation.
| |
| | | | |
| | ===SECURING AUTHENTICATION FLOWS USING A DECENTRALIZED IDENTIFIER (17710220)=== | | ===SECURING AUTHENTICATION FLOWS USING A DECENTRALIZED IDENTIFIER (17710220)=== |
| Line 715: |
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| | '''Inventor''' | | '''Inventor''' |
| | Brandon Brian MURDOCH | | Brandon Brian MURDOCH |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a process involving a digital wallet, an identification provider, and a verifiable claim issuer. The digital wallet generates an identification value for the owner of a decentralized identifier (DID). It then requests an authentication token from the identification provider using this identification value. Once the identification provider validates the request, the digital wallet receives the authentication token. This token allows the digital wallet to authenticate itself with the verifiable claim issuer, which also includes the identification value. The digital wallet then requests one or more verifiable claims from the verifiable claim issuer, using the authentication token and the DID. If the verifiable claim issuer validates the authentication token and identification value, the digital wallet receives the requested verifiable claims.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A digital wallet generates an identification value associated with a DID of a DID owner. The digital wallet generates a first request including the identification value for an authentication token from an identification provider. The first request is provided to the identification provider. The digital wallet receives, in response to the identification provider validating the first request, the authentication token that authenticates the digital wallet with a verifiable claim issuer including the identification value from the identification provider. The digital wallet generates a second request for one or more verifiable claims from the verifiable claim issuer. The second request includes the DID and authentication token including the identification value. In response to the verifiable claim issuer validating the authentication token and the identification value, one or more verifiable claims from the verifiable claim issuer are received by the digital wallet.
| |
| | | | |
| | ===PROXY SERVICES FOR THE SECURE UPLOAD OF FILE SYSTEM TREE STRUCTURES (18118863)=== | | ===PROXY SERVICES FOR THE SECURE UPLOAD OF FILE SYSTEM TREE STRUCTURES (18118863)=== |
| Line 726: |
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| | '''Inventor''' | | '''Inventor''' |
| | Itamar AZULAY | | Itamar AZULAY |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a method for securely uploading file-system tree structures using proxy services. When a client device wants to upload content to a storage cloud provider, a web security service receives this request. The proxy service then scans the content for security and privacy issues while it is still stored on the client device. If any concerns are identified, the proxy service takes appropriate actions to mitigate the security and privacy risks.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | The disclosure is directed towards proxy services for the secure uploading of file-system tree structures. A method includes receiving, at a web security service, an indication that client device to upload content to a storage cloud provider. The proxy service performs a security scan of the content while the content is stored on the client device. A security and/or a privacy concern is identified in the content stored on the client device. A security and/or privacy mitigation action is performed in response to identifying the security and/or privacy concern.
| |
| | | | |
| | ===Packet Capture Using Fixed Encryption Key (17713520)=== | | ===Packet Capture Using Fixed Encryption Key (17713520)=== |
| Line 737: |
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| | '''Inventor''' | | '''Inventor''' |
| | Tomas WEINFURT | | Tomas WEINFURT |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a computer method that involves receiving data from an application, diverting the received data to an input/output layer, and generating data packets from the received data. Mock packet headers are created with packet formatting and address information, and these headers are combined with the data packets to form transport packets. The transport packets are then encrypted using a fixed key. These encrypted transport packets are provided to a network debug tool, which uses a public key to decrypt them and inspect their contents.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A computer implemented method includes receiving data from an application layer resulting in received data. The received data is diverted to an input/output layer outside a communication stack and data packets are generated from the received data. Mock packet headers are fabricated with packet formatting and address corresponding to an underlying transport layer. Corresponding mock packet headers are concatenated with the data packets to form transport packets which are encrypted using a fixed key. The transport packets are provided to a network debug tool for decryption using a public key for execution of the network debug tool to inspect the transport packets.
| |
| | | | |
| | ===EVENT-LEVEL DATA PRIVACY FOR STREAMING POST ANALYTICS DATA (17709318)=== | | ===EVENT-LEVEL DATA PRIVACY FOR STREAMING POST ANALYTICS DATA (17709318)=== |
| Line 748: |
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| | '''Inventor''' | | '''Inventor''' |
| | Ryan M. Rogers | | Ryan M. Rogers |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a technology that ensures privacy for event-level data in streaming post analytics. It involves receiving a data stream with count data collected over a period of time. The technology computes a breakdown of the true count, which includes various sub-counts of non-public user interactions on a post. To protect privacy, a noisy count breakdown is created by applying a differential privacy mechanism to the sub-counts. This noisy count breakdown is then streamed to a computing device instead of the true count breakdown. The technology also considers attributes associated with the non-public user interactions, such as different possible values for a particular attribute.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Technologies for providing event-level data privacy for streaming post analytics data include, in some embodiments, receiving a data stream that includes instances of count data collected over a time interval, computing a true count breakdown that includes a set of sub-counts of non-public user interface interactions on the post, creating a noisy count breakdown by applying at least one differential privacy mechanism to the set of sub-counts, and streaming the noisy count breakdown instead of the true count breakdown to a computing device. At least one of the sub-counts is a count that is associated with a particular value of an attribute that has different possible values. The attribute is associated with the non-public user interface interactions on the post.
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| | | | |
| | ===RESOURCE MANAGEMENT FOR RELIABILITY (17826077)=== | | ===RESOURCE MANAGEMENT FOR RELIABILITY (17826077)=== |
| Line 759: |
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| | '''Inventor''' | | '''Inventor''' |
| | Keith Stuart WANSBROUGH | | Keith Stuart WANSBROUGH |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a method used by a health service to update a domain name system (DNS) in order to allow clients to allocate service requests to multiple service instances. These service instances use a microservice architecture. The health service collects outcome data from the service instances and calculates a status indicator for each instance. This status indicator is based on internal checks performed within the microservice architecture and heuristic calculations on service request performance data. Once the status indicator is calculated, the health service updates the DNS dynamically based on this indicator.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A method performed by a health service configured to update a domain name system (DNS) to enable clients, which use the DNS, to allocate service requests to a plurality of service instances which provide the service wherein each service instance comprises a microservice architecture is presented. The health service requests outcome data from at least one of the service instances, and calculates a status indicator for the service instance, wherein the status indicator is calculated based on results from internal recursive checks performed throughout the microservice architecture of the service instance and heuristic calculations performed on service request performance data. After calculating the status indicator, the health service triggers a dynamic update to the DNS according to the calculated status indicator.
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| | | | |
| | ===ADJUSTING PARTICIPANT GAZE IN VIDEO CONFERENCES (18205894)=== | | ===ADJUSTING PARTICIPANT GAZE IN VIDEO CONFERENCES (18205894)=== |
| Line 770: |
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| | '''Inventor''' | | '''Inventor''' |
| | Eric Chris Wolfgang SOMMERLADE | | Eric Chris Wolfgang SOMMERLADE |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes methods and systems for adjusting the gaze of participants in a video conference. The system receives information about image adjustments for a video stream of a first participant. It identifies the location where the first participant's images are displayed in the communication application. Based on the received information, it determines the location where the images of a second participant should be displayed, taking into account that the first participant's gaze is directed towards the second participant. The system then calculates the eye gaze direction of the first participant based on the location of the second participant's images. It generates adjusted images to match the desired eye gaze direction of the first participant and replaces the original images in the video stream with the adjusted ones.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Methods and systems for applying gaze adjustment techniques to participants in a video conference are disclosed. Some examples may include: receiving, at computing system, image adjustment information associated with a video stream including images of a first participant, identifying, for a display layout of a communication application, a location displaying the images of the first participant, determining, based on the received image adjustment information, a location displaying images of a second participant for the display layout, the received image adjustment information indicating that an eye gaze of the first participant being directed toward the second participant, computing an eye gaze direction of the first participant based on the location displaying images of the second participant, generating gaze-adjusted images based on the desired eye gaze direction of the first participant and replacing the images within the video stream with the gaze-adjusted images.
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| | | | |
| | ===REINFORCEMENT LEARNING BASED RATE CONTROL (18013240)=== | | ===REINFORCEMENT LEARNING BASED RATE CONTROL (18013240)=== |
| Line 781: |
Line 377: |
| | '''Inventor''' | | '''Inventor''' |
| | Jiahao LI | | Jiahao LI |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a solution for rate control in video encoding using reinforcement learning. It explains that the solution determines the encoding state of a video encoder and uses a reinforcement learning model to determine the encoding parameter for rate control. By encoding a second video unit based on this parameter, the solution aims to improve the quality of experience (QOE) in real-time communication while reducing computation overhead.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Implementations of the subject matter described herein provide a solution for rate control based on reinforcement learning. In this solution, an encoding state of a video encoder is determined, the encoding state being associated with encoding of a first video unit by the video encoder. An encoding parameter associated with rate control in the video encoder is determined by a reinforcement learning model and based on the encoding state of the video encoder. A second video unit different from the first video unit is encoded based on the encoding parameter. In this way, it is possible to achieve a better quality of experience (QOE) for real time communication with computation overhead being reduced.
| |
| | | | |
| | ===CAMERA COMPRISING LENS ARRAY (17657865)=== | | ===CAMERA COMPRISING LENS ARRAY (17657865)=== |
| Line 792: |
Line 382: |
| | '''Inventor''' | | '''Inventor''' |
| | Curtis Alan TESDAHL | | Curtis Alan TESDAHL |
| − |
| |
| − | '''Brief explanation'''
| |
| − | The abstract describes a technology that involves capturing images of the eye using a camera with multiple lenses. The camera has an array of lenses, and each lens focuses the image of the eye onto a different part of the image sensor. This allows for detailed and accurate eye imaging on a near-eye system.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | Examples are disclosed herein that relate to eye imaging on a near-eye system using an eye-imaging camera that includes an array of lenses. One example provides a near-eye system, comprising an eye-imaging camera comprising an image sensor, and an array of lenses, each lens of the array of lenses configured to focus an image of an eye onto a different area of the image sensor than each other lens of the array of lenses.
| |
| | | | |
| | ===FOLDED GRAPHITE FINS FOR HEATSINKS (17710128)=== | | ===FOLDED GRAPHITE FINS FOR HEATSINKS (17710128)=== |
| Line 803: |
Line 387: |
| | '''Inventor''' | | '''Inventor''' |
| | Luke Thomas GREGORY | | Luke Thomas GREGORY |
| − |
| |
| − | '''Brief explanation'''
| |
| − | This abstract describes a thermal management device that consists of a heat spreader and a folded graphite sheet. The heat spreader collects heat from a heat source, while the folded graphite sheet is connected to the heat spreader to receive and release the heat. The folded graphite sheet is made up of a first fin, a second fin, and a connecting segment between them. Both fins are oriented vertically away from the heat spreader. The folded graphite sheet is continuous throughout the first fin, the segment, and the second fin.
| |
| − |
| |
| − | '''Abstract'''
| |
| − | A thermal management device includes a heat spreader and a folded graphite sheet. The heat spreader is configured to receive heat from a heat source. The folded graphite sheet is connected to the heat spreader to receive and exhaust heat from the heat spreader. The folded graphite sheet includes a first fin, a second fin, and a segment connecting the first fin and second fin. The first fin is oriented at least partially vertically away from the heat spreader. The second fin is oriented at least partially vertically away from the heat spreader. The folded graphite sheet is continuous through the first fin, the segment, and the second fin.
| |
