Abstract: A method for controlling a vehicle transmission system having a clutch system includes generating a torque-pressure (T-P) gain deviation based on a T-F characteristic and a nominal T-F characteristic for the clutch system, generating a pressure magnitude deviation based on the set of pressure values and the set of nominal pressure values, determining whether a T-F characteristic deviates from the nominal T-F characteristic based on the T-P gain deviation and the pressure magnitude deviation, identifying the T-F characteristic as deviating in response to the T-F characteristic departing from the nominal transfer characteristic, and issuing a notification regarding the deviating T-F characteristic to perform a corrective action related to the clutch system.

Abstract: Disclosed embodiments may include a method that may include receiving a corpus of unlabeled text documents, generating, using the first machine learning model, a first classification of each unlabeled text document in the corpus of unlabeled text documents as positive or negative, defining, using the first machine learning model and based on the first classification, a first subset of the unlabeled text documents and a second subset of the unlabeled text documents, generating, using the second machine learning model, a second classification of each unlabeled text document in the first subset of the unlabeled text documents as positive or negative, generating, using the third machine learning model, a third classification of each unlabeled text document in the second subset of the unlabeled text documents as positive or negative, and modifying the first classification, based on the second classification and the third classification, to create a fourth classification.

Abstract: A lithium (Li)-containing compound is a lipophilic Li salt, and each molecule of the lipophilic Li salt has at least one lipophilic endgroup. In addition, a scintillator material includes an organic liquid and a lipophilic Li salt, where the lipophilic Li salt is solubilized in the organic liquid. The scintillator material includes at least one fluorescent dye, the dye being effective to provide scintillation upon exposure to radiation. The scintillator material exhibits an optical response signature for thermal neutrons that is different than an optical response signature for fast neutrons.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.

Abstract: A formulation for forming a styrene-based scintillator using light-directed additive manufacturing techniques includes a base monomer, a primary dye, a secondary dye, and a cationic photoinitiator. The base monomer includes one or more styrene-derivative monomers.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.

Abstract: An apparatus for network switching may include a plurality of input ports, a plurality of output ports, and a subset of pre-configured interconnection patterns including some but not all of the possible interconnection patterns between the input ports and the output ports. The apparatus may be communicatively coupled to a network via the input ports and/or the output ports. The apparatus may be configured to switch to a first interconnection pattern and a second interconnection pattern from the subset of pre-configured interconnection patterns. The first interconnection pattern and the second interconnection pattern may each provide a set of connections between the input ports and the output ports. At least one signal between the input ports and the output ports may be transmitted via the first interconnection pattern and/or the second interconnection pattern. Related methods are also provided.

Abstract: Disclosed embodiments may include a method that may include receiving a corpus of unlabeled text documents, generating, using the first machine learning model, a first classification of each unlabeled text document in the corpus of unlabeled text documents as positive or negative, defining, using the first machine learning model and based on the first classification, a first subset of the unlabeled text documents and a second subset of the unlabeled text documents, generating, using the second machine learning model, a second classification of each unlabeled text document in the first subset of the unlabeled text documents as positive or negative, generating, using the third machine learning model, a third classification of each unlabeled text document in the second subset of the unlabeled text documents as positive or negative, and modifying the first classification, based on the second classification and the third classification, to create a fourth classification.

Abstract: A support frame assembly mounted to a narrow track vehicle to enhance stability during turns is provided. The support frame assembly includes a pivot frame assembly coupled to the narrow track vehicle and having a horizontal beam connected to a vertical beam, the horizontal beam supporting the seat of the narrow track vehicle thereon, a fixed frame assembly coupled to the narrow track vehicle and having a horizontal beam pivotably mounted to the vertical beam of the pivot frame assembly, and a pair of struts coupled to the pivot frame assembly and fixed frame assembly. The pair of struts apply counteracting forces on the vertical beam of the pivot frame assembly in response to pivotal movement of the pivot frame assembly relative to the fixed frame assembly.

Abstract: An ATM device may receive a request to process an ATM transaction; dispense, via an instrument dispenser, a plurality of instruments based on the request; perform image segmentation of one or more images of an area surrounding the instrument dispenser, wherein the image segmentation is performed using a deep learning network trained using synthetic models of hands; detect, based on performing the image segmentation, that a user's hand approaches the instrument dispenser after dispensing the plurality of instruments; determine, after dispensing the plurality of instruments and after detecting that the user's hand approaches the instrument dispenser, that a portion of the plurality of instruments is present at the instrument dispenser; and perform one or more actions based on determining that the portion of the plurality of instruments is present at the instrument dispenser.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.

Abstract: A downhole reciprocating pump configured for deployment within a tubing string. The reciprocating pump includes a pump barrel, a plunger inside the pump barrel, a lower seating nipple connected within a lower portion of the tubing string and a lower hold-down connected to the pump barrel. The lower hold-down is configured for a mechanical latching engagement with the lower seating nipple. The reciprocating pump also includes an upper seating nipple connected within the tubing string above the lower seating nipple. The upper seating nipple is longer than the lower seating nipple. The reciprocating pump further includes an upper hold-down that has one or more seals that contact an interior surface of the upper seating nipple.

Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.

Abstract: A system for guiding image sensor angle settings in different environments. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include obtaining a plurality of synthetic images, the synthetic images representing a plurality of scenes; training a classification model to classify, based on the synthetic images, a plurality of images captured from an environment of a user by an image sensor; determining, based on the classification, whether the image sensor is positioned at a predetermined angle; and adjusting, based on the determination, a position of the image sensor.

Abstract: An apparatus for network switching may include a plurality of input ports, a plurality of output ports, and a subset of pre-configured interconnection patterns including some but not all of the possible interconnection patterns between the input ports and the output ports. The apparatus may be communicatively coupled to a network via the input ports and/or the output ports. The apparatus may be configured to switch to a first interconnection pattern and a second interconnection pattern from the subset of pre-configured interconnection patterns. The first interconnection pattern and the second interconnection pattern may each provide a set of connections between the input ports and the output ports. At least one signal between the input ports and the output ports may be transmitted via the first interconnection pattern and/or the second interconnection pattern. Related methods are also provided.

Abstract: A system for guiding image sensor angle settings in different environments. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include obtaining a plurality of synthetic images, the synthetic images representing a plurality of scenes; training a classification model to classify, based on the synthetic images, a plurality of images captured from an environment of a user by an image sensor; determining, based on the classification, whether the image sensor is positioned at a predetermined angle; and adjusting, based on the determination, a position of the image sensor.

Abstract: A system for guiding image sensor angle settings in different environments. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include obtaining a plurality of synthetic images, the synthetic images representing a plurality of scenes; training a classification model to classify, based on the synthetic images, a plurality of images captured from an environment of a user by an image sensor; determining, based on the classification, whether the image sensor is positioned at a predetermined angle; and adjusting, based on the determination, a position of the image sensor.

Abstract: A latch assembly for mounting in an opening of a door and for releasably latching the door to a door frame. The latch assembly includes a housing that is mountable to the opening of the door. A lever is rotatably coupled to the housing between a deployed position and a retracted position. A lock plug is rotatably mounted within the housing, the lock plug having one end for receiving either a tool or key, and an opposite end having an engagement surface. A latching member is movably coupled to the housing, and is engaged with both the rotatable lock plug and the lever in the retracted position of the lever. A torsion spring biases the lock plug back to a starting position after the lock plug is rotated from the starting position using the tool or the key.

Abstract: An ATM device may receive a request to process an ATM transaction; dispense, via an instrument dispenser, a plurality of instruments based on the request; perform image segmentation of one or more images of an area surrounding the instrument dispenser, wherein the image segmentation is performed using a deep learning network trained using synthetic models of hands; detect, based on performing the image segmentation, that a user's hand approaches the instrument dispenser after dispensing the plurality of instruments; determine, after dispensing the plurality of instruments and after detecting that the user's hand approaches the instrument dispenser, that a portion of the plurality of instruments is present at the instrument dispenser; and perform one or more actions based on determining that the portion of the plurality of instruments is present at the instrument dispenser.

Abstract: In one aspect, there is provided a display. The display may include a waveguide layer, a first active layer, a redirecting layer, and a lenset layer.