Abstract: Camera head apparatus, systems, and methods for providing wide angle/panoramic images and/or video of the interior of pipes or other cavities using multiple imaging and illumination modules are disclosed.

Abstract: A computing system for automatically initiating reversal of a previously-issued electronic instruction is provided. The computing system includes a processor in communication with a memory.

Abstract: Apparatus, systems, and methods are disclosed for tracking movement over the ground or other surfaces using two or more spaced apart cameras and an associated processing element to detect ground features in images from the cameras and determine tracking parameters based on the position of the detected ground features in the images.

Abstract: A system includes a robot configured to transfer either one of a substrate and an edge ring within a substrate processing system, a substrate aligner configured to adjust a rotational position of either one of the substrate or the edge ring relative to an end effector of the robot, and a carrier plate configured to support the edge ring. The robot is configured to retrieve the carrier plate with the end effector, retrieve the edge ring using the carrier plate supported on the end effector, and transfer the carrier plate and the edge ring to the substrate aligner.

Abstract: A device may transmit questionnaires to a set of client devices, wherein the questionnaires include a set of questions that relate to an internal entity experience attribute and/or an external entity experience attribute. The device may receive a set of questionnaire responses and correlate the set of questionnaire responses with contextual data relating to an entity. The device may process, using a machine learning model trained based on data relating to one or more other entities, the set of questionnaire responses and the contextual data to identify a set of features and a set of feature ranks. The device may select a subset of features based on the set of feature ranks and a set of influence thresholds. The device may generate a set of recommendations associated with the subset of features and communicate with one or more other devices to implement the set of recommendations.

Abstract: A system for categorizing images is provided. The system is programmed to store a first training set of images. Each image of the first training set of images is associated with an image category of a plurality of image categories. The system is further programmed to analyze each image of the first training set of images to determine one or more features associated with each of the plurality of image categories and receive a second training set of images. The second training set of images includes one or more errors. The system is also programmed to analyze each image of the second training set of images to determine one or more features associated with an error category and generate a model to identify each of the image categories based on the analysis such that the model includes the error category in the plurality of image categories.

Abstract: Described herein are chargeback settlement processing systems and methods. A chargeback settlement computing device is configured to store a dispute table including a dispute record associated with a first chargeback request associated with a first chargeback transaction. The dispute record includes an account identifier, a chargeback transaction amount, and a unique chargeback identifier. The computing device is also configured to receive (i) a clearing detail record including a unique chargeback reference number associated with clearing/settlement of the chargeback transaction and chargeback transaction data, and (ii) a chargeback response including the chargeback identifier, the chargeback reference number, and chargeback transaction data.

Abstract: A system for categorizing images is provided. The system is programmed to store a first training set of images. Each image of the first training set of images is associated with an image category of a plurality of image categories. The system is further programmed to analyze each image of the first training set of images to determine one or more features associated with each of the plurality of image categories and receive a second training set of images. The second training set of images includes one or more errors. The system is also programmed to analyze each image of the second training set of images to determine one or more features associated with an error category and generate a model to identify each of the image categories based on the analysis such that the model includes the error category in the plurality of image categories.

Abstract: Camera head apparatus, systems, and methods for providing wide angle/panoramic images and/or video of the interior of pipes or other cavities using multiple imaging and illumination modules are disclosed.

Abstract: A ring storage station used for delivering a consumable part to a substrate processing system includes a housing that includes a base plate and a rotating plate disposed over the base plate. An end-effector opening is disposed at a first side of the housing and a service window opening is disposed at a second side of the housing. A set of finger support structures is connected to the rotating plate. Each finger support structure includes a support column and support fingers disposed thereon. At least two of the set of columns have support fingers with index pins to radially align consumable parts when disposed in the ring storage station. In one configuration, consumable parts may be designed to match the rotation angle engagement to ensure catching the angle alignment between ring storage and process module.

Abstract: Apparatus, systems, and methods are disclosed for utility locating with tracking of movement over the ground or other surfaces using a dodecahedral antenna array and a stereo-optical ground tracker having two or more spaced apart cameras and an associated processing element to detect ground features in images from the cameras and determine tracking parameters based on the position of the detected ground features.

Abstract: Described herein are chargeback settlement processing systems and methods. A chargeback settlement computing device is configured to store a dispute table including a dispute record associated with a first chargeback request associated with a first chargeback transaction. The dispute record includes an account identifier, a chargeback transaction amount, and a unique chargeback identifier. The computing device is also configured to receive (i) a clearing detail record including a unique chargeback reference number associated with clearing/settlement of the chargeback transaction and chargeback transaction data, and (ii) a chargeback response including the chargeback identifier, the chargeback reference number, and chargeback transaction data.

Abstract: A system for categorizing images is provided. The system is programmed to store a first training set of images. Each image of the first training set of images is associated with an image category of a plurality of image categories. The system is further programmed to analyze each image of the first training set of images to determine one or more features associated with each of the plurality of image categories and receive a second training set of images. The second training set of images includes one or more errors. The system is also programmed to analyze each image of the second training set of images to determine one or more features associated with an error category and generate a model to identify each of the image categories based on the analysis such that the model includes the error category in the plurality of image categories.

Abstract: A computing system for automatically initiating a chargeback transaction from a plurality of processed transactions is provided.

Abstract: Described herein are chargeback settlement processing systems and methods. A chargeback settlement computing device is configured to store a dispute table including a dispute record associated with a first chargeback request associated with a first chargeback transaction. The dispute record includes an account identifier, a chargeback transaction amount, and a unique chargeback identifier. The computing device is also configured to receive (i) a clearing detail record including a unique chargeback reference number associated with clearing/settlement of the chargeback transaction and chargeback transaction data, and (ii) a chargeback response including the chargeback identifier, the chargeback reference number, and chargeback transaction data.

Abstract: A device may transmit questionnaires to a set of client devices, wherein the questionnaires include a set of questions that relate to an internal entity experience attribute and/or an external entity experience attribute. The device may receive a set of questionnaire responses and correlate the set of questionnaire responses with contextual data relating to an entity. The device may process, using a machine learning model trained based on data relating to one or more other entities, the set of questionnaire responses and the contextual data to identify a set of features and a set of feature ranks. The device may select a subset of features based on the set of feature ranks and a set of influence thresholds. The device may generate a set of recommendations associated with the subset of features and communicate with one or more other devices to implement the set of recommendations.

Abstract: Described herein are chargeback settlement processing systems and methods. A chargeback settlement computing device is configured to store a dispute table including a dispute record associated with a first chargeback request associated with a first chargeback transaction. The dispute record includes an account identifier, a chargeback transaction amount, and a unique chargeback identifier. The computing device is also configured to receive (i) a clearing detail record including a unique chargeback reference number associated with clearing/settlement of the chargeback transaction and chargeback transaction data, and (ii) a chargeback response including the chargeback identifier, the chargeback reference number, and chargeback transaction data.

Abstract: A chargeback settlement processing (CSP) computer system for determining a gain or loss in a chargeback transaction is provided, that includes a memory device and a processor in communication with the memory device. The processor is programmed to transmit to a payment card network for settlement at least one chargeback transaction file corresponding to at least one received chargeback transaction, associated with an original transaction settled using a first currency exchange rate. The at least one chargeback transaction file includes a unique file identifier. A reconciliation message received from the payment card network includes at least one settlement amount, determined at a second currency exchange rate, for the at least one chargeback transaction and the unique file identifier. The at least one chargeback transaction file is matched to the at least one settlement amount, using the unique file identifier, to determine whether a net gain or a net loss occurred.

Abstract: Camera head apparatus, systems, and methods for providing wide angle/panoramic images and/or video of the interior of pipes or other cavities using multiple imaging and illumination modules are disclosed.

Abstract: In an embodiment, a whistle apparatus includes an edible whistle component and an aperture and a compressible body containing a receptacle configured to receive the edible whistle component, the receptacle portion including a passage. When an edible whistle component is secured to the receptacle of the compressible body and when the compressible body is compressed, gas is urged through both the aperture and the passage to emit a sound.