Abstract: Provided is a display device. The display device includes a display substrate and a drive assembly; wherein the display substrate has a first bonding region, and the drive assembly has a second bonding region corresponding to the first bonding region; and the display substrate includes a first limiting assembly disposed outside the first bonding region, and the drive assembly includes a second limiting assembly disposed outside the second bonding region and engaged with the first limiting assembly; wherein the first limiting assembly is configured to engage with the second limiting assembly to restrict relative movement between the drive assembly and the display substrate during bonding the first bonding region to the second bonding region.

Abstract: Provided is a display device. The display device includes a bending adhesive layer, a backlight module and a display module; the backlight module and the display module are connected through the bending adhesive layer; an air flow passage is disposed between the display module and the bending adhesive layer, and a pressure zone exists between the backlight module and the bending adhesive layer; the air flow passage is configured to discharge a bubble existed in the pressure zone.

Abstract: A control circuit can access inspection results from an inspection of a first component and then input those inspection results to a first machine learning model. The inspection results include potential wear indications. By one approach, that first machine learning model is trained using a training corpus that includes inspection results for previously inspected components that are at least similar to the first component. The first machine learning model can output assessment information that, by one approach, identifies some of the potential wear indications as being relevant. By one approach, the aforementioned assessment information may be input a second machine learning model that is trained using a training corpus that includes historical results from previous inspections of the same first component and wherein the second machine learning model outputs prediction information regarding whether a repeated physical processing of the first component will yield a particular result.

Abstract: A conductive adhesive film is disclosed. The conductive adhesive film includes a first film layer and a conductive particle layer. The first film layer has a plurality of electrode contact regions and a non-contact region separating the plurality of electrode contact regions. The first film layer has a plurality of gap structures, and the plurality of gap structures are located at least in the non-contact region. The conductive particle layer is located on a side of the first film layer. The conductive particle layer includes conductive particles. An orthographic projection of the conductive particles on the first film layer overlaps with at least a portion of each electrode contact region.

Abstract: A method for smelting low-phosphorus high-manganese steel based on reduction dephosphorization of ferromanganese is provided in the present application, relating to the technical field of high-manganese steel smelting, where the dephosphorization of ferromanganese is carried out under reducing atmosphere conditions through mediate-frequency induction furnace to obtain molten ferromanganese with lower phosphorus content, which is subsequently mixed with low phosphorus molten steel obtained by smelting in oxidative period of electric arc furnace in LF ladle refining furnace to make the Mn content of steel reach the requirement of high-manganese steel, and smelting is carried out under the condition of reducing atmosphere by adjusting the composition and temperature of the molten steel to meet the requirements of the target composition of the steel grade before tapping the steel.

Abstract: Examples described herein relate to offload reliable transport management to a network interface device and store packets to be resent, based on received packet receipt acknowledgements (ACKs), into one or more kernel space queues that are also accessible in user space.

Abstract: The present application discloses an electronic device including a housing, support plates and a display panel. The housing is recessed inward to form one or more clearances penetrating the housing along a first direction. A number of the support plates is at least two, and one clearance is correspondingly arranged below adjoining parts of two adjacent support plates. The support plates are configured to support the display panel. The display panel is switchable between a folded position and an unfolded position. When the display panel is in the unfolded position, first surfaces of the support plates that abut against the display panel are flush.

Abstract: A system for polishing a surface of a component includes a motorized apparatus including a body, a drive system coupled to the body, and an arm including a proximal end coupled to the body and a distal end opposite the proximal end. The motorized apparatus further includes a tool coupled to the distal end of the arm. The tool is configured to polish the surface of the component. The motorized apparatus also includes an actuator coupled to the arm. The system also includes a controller configured to position the tool relative to the component by positioning at least one of the body and the arm relative to the component to reach the target area on the component while maintaining a distance between the tool and the body that is less than a threshold distance. The threshold distance is less than a full reach of the arm and is determined to prevent vibrations of the tool and the arm from exceeding a predefined level.

Abstract: A method of inspecting a component using an image retrieval module includes storing an inspection image file in a memory and identifying a region of interest in the inspection image file. The method further includes accessing a database storing image files and determining feature vectors associated with the image files. The method also includes determining a hash code for each image file based on the feature vectors and classifying a subset of image files as relevant based on the hash codes. The method further includes sorting the subset of image files based on the feature vectors and generating search results based on the sorted subset of image files. The image retrieval module includes a convolutional neural network configured to learn from the determination of the feature vectors and increase the accuracy of the image retrieval module in classifying the image files.

Abstract: Provided is a system and method for detecting source(s) of oscillation on a power grid. In one example, the method may include receiving measurements from one or more sensors on a power grid, the measurements including data of an oscillation within the power grid, determining, via execution of one or more machine learning model, a candidate set of power system components disposed on the power grid that are candidates for being the source(s) of the oscillation, identifying, via execution of an optimization model, a component from among the candidate set of power system components which is the source (e.g., location, controller type, and/or asset type) of the oscillation, and displaying, via a user interface, information about the identified component.

Abstract: A method of inspecting a component includes storing at least one inspection image file in a memory and receiving a search request associated with the at least one inspection image file. The method also includes accessing a database including a plurality of image files, comparing the hash code of the at least one inspection image file to the hash code of each image file of the plurality of image files, and identifying a first subset of image files based on the hash code comparison. The method also includes comparing the feature data of the at least one inspection image file to the feature data of each image file of the first subset of image files and classifying a second subset of image files as relevant based on the feature data comparison. The method further includes generating search results based on the second subset of image files.

Abstract: A method of inspecting a component using an image retrieval module includes storing an inspection image file in a memory and identifying a region of interest in the inspection image file. The method further includes accessing a database storing image files and determining feature vectors associated with the image files. The method also includes determining a hash code for each image file based on the feature vectors and classifying a subset of image files as relevant based on the hash codes. The method further includes sorting the subset of image files based on the feature vectors and generating search results based on the sorted subset of image files. The image retrieval module includes a convolutional neural network configured to learn from the determination of the feature vectors and increase the accuracy of the image retrieval module in classifying the image files.

Abstract: A method of inspecting a component includes storing at least one inspection image file in a memory and receiving a search request associated with the at least one inspection image file. The method also includes accessing a database including a plurality of image files, comparing the hash code of the at least one inspection image file to the hash code of each image file of the plurality of image files, and identifying a first subset of image files based on the hash code comparison. The method also includes comparing the feature data of the at least one inspection image file to the feature data of each image file of the first subset of image files and classifying a second subset of image files as relevant based on the feature data comparison. The method further includes generating search results based on the second subset of image files.

Abstract: Systems and methods for facilitating proximity detection and location tracking using a hub or bridge are disclosed. An example apparatus is to receive a message from a beacon at a second location within a proximity area of the apparatus, the message indicative of the second location and identifying the beacon; and relay the message to a location server to determine asset location.

Abstract: A method of inspecting a component using an image inspection controller that includes a processor communicatively coupled to a memory includes classifying each sample image in a first database as a first sample or a second sample using a classification module, extracting at least one class generic feature from each first sample to generate a plurality of class generic features, and extracting at least one class specific feature from each second sample to generate a plurality of class specific features. The method further includes combining the class generic features and the class specific features to generate a plurality of supplemental images. The method further includes storing the sample images and the supplemental images in a second database, classifying each sample image and each supplemental image, capturing at least one image of the component using a camera, and identifying at least one feature of the component in the at least one image of the component using the classification module.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to facilitate proximity detection and location tracking. An example method includes receiving messages collected by a badge in an environment, the messages including signal strength and a timestamp. The example method also includes assigning a location in the environment to the badge based on a first subset of the messages. The example method also includes identifying an asset in a second subset of the messages. The example method also includes updating a current location associated with the asset based on a relative proximity of the asset to the badge, wherein the current location corresponds to a first time and the updated location corresponds to a second time, and wherein a change in location between the current location and the updated location indicates movement of the asset in the environment.

Abstract: A method of inspecting a component using an image inspection controller that includes a processor communicatively coupled to a memory includes classifying each sample image in a first database as a first sample or a second sample using a classification module, extracting at least one class generic feature from each first sample to generate a plurality of class generic features, and extracting at least one class specific feature from each second sample to generate a plurality of class specific features. The method further includes combining the class generic features and the class specific features to generate a plurality of supplemental images. The method further includes storing the sample images and the supplemental images in a second database, classifying each sample image and each supplemental image, capturing at least one image of the component using a camera, and identifying at least one feature of the component in the at least one image of the component using the classification module.

Abstract: Systems and methods for facilitating proximity detection and location tracking using a hub or bridge are disclosed. An example apparatus is to receive a message from a beacon at a second location within a proximity area of the apparatus, the message indicative of the second location and identifying the beacon; and relay the message to a location server to determine asset location.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to facilitate proximity detection and location tracking. An example method includes receiving messages collected by a badge in an environment, the messages including signal strength and a timestamp. The example method also includes assigning a location in the environment to the badge based on a first subset of the messages. The example method also includes identifying an asset in a second subset of the messages. The example method also includes updating a current location associated with the asset based on a relative proximity of the asset to the badge, wherein the current location corresponds to a first time and the updated location corresponds to a second time, and wherein a change in location between the current location and the updated location indicates movement of the asset in the environment.

Abstract: A system for polishing a surface of a component includes a motorized apparatus including a body, a drive system coupled to the body, and an arm including a proximal end coupled to the body and a distal end opposite the proximal end. The motorized apparatus further includes a tool coupled to the distal end of the arm. The tool is configured to polish the surface of the component. The motorized apparatus also includes an actuator coupled to the arm. The system also includes a controller configured to position the tool relative to the component by positioning at least one of the body and the arm relative to the component to reach the target area on the component while maintaining a distance between the tool and the body that is less than a threshold distance. The threshold distance is less than a full reach of the arm and is determined to prevent vibrations of the tool and the arm from exceeding a predefined level.