Abstract: Aspects of this disclosure relate to systems and methods to determine whether an application is misconfigured or malicious using smart contracts stored on a distributed ledger and a transferred deep learning system. A smart contract is generated and assigned rules for monitoring an application session on a user computing device when an application session associated with the application is initiated. The smart contract denies or grants the application session permission to access user data and shuts down the application session when a malicious indication is detected in configuration data associated with the application based on rules assigned to the smart contract. The malicious indication is output by a deep learning module trained on historical configuration data associated with the application. The deep learning module transfers layers to an enterprise deep learning module on an enterprise platform to determine a misconfiguration indication indicating the configuration data is misconfigured.

Abstract: Arrangements for remote device control and transaction processing are provided. In some aspects, a local computing device may initiate a communication session with the self-service kiosk. The local computing device may capture self-service kiosk identifying data and may generate a deep link to an application. The local computing device may transmit the deep link and self-service kiosk identifying information to a remote computing device. An indication of selection of the deep link may be received by the local computing device and a remote transaction processing session may be initiated at the self-service kiosk. The self-service kiosk may transmit a user interface for display by the remote computing device. An option from the user interface may be selected for processing. The self-service kiosk may process the selected option, send a notification of transaction completion to the remote user computing device and terminate the communication session with the local user computing device.

Abstract: A smart-dust information security and energy optimization process/machine/system is disclosed for use with an ATM. Tiny microelectromechanical systems (MEMS) less than 1 mm in size are deployed and distributed in and around the ATM internal and external components. The MEMS include various sensors to detect component malfunctions and identify security threats (e.g., card skimmers), and also to place the ATM in a reduced energy state whenever possible. MEMS interoperable components and sensors may include, inter alia, batteries, wireless transmitters/receivers, processors, memory, analog-to-digital converters, LIDAR, photo detectors, vibration detectors, motion detectors, wireless signal detectors for detecting Bluetooth or RFID signals, temperature sensors, humidity sensor, a power consumption/induced electromagnetic energy sensors, piezoelectric sensors, sound sensors, etc.

Abstract: Apparatus and methods for a li-fi payment network are provided. A customer's device may communicate, directly or through intermediate devices and computer systems, over a li-fi network with a point-of-sale terminal. A bill may be transmitted to the customer's device over the li-fi network. The customer may select an option to pay the bill. The selection, along with information to authorize and process the payment, may be transmitted over the li-fi network to the POS terminal. The POS terminal may process the payment and generate a receipt. The receipt may be transmitted to the customer's device over the li-fi network.

Abstract: An electronic bill may be generated, transmitted, and paid remotely at a POS using a UWB-compatible user device. The location of the user device may be detected leveraging UWB technology at the POS. The bill may be pushed to the user device over a MEMS network of sensor nodes at the POS. An optimal route over the sensor nodes may be selected so that the electronic bill is directed to a sensor node in proximity to the user device. The selected route may minimize the number of sensor nodes over which the bill must pass. The route may be dynamically changed when the user device is moved from one location to another at the POS. The customer may specify an electronic payment method in response to receiving the bill or the customer may have pre-specified the payment method. An electronic confirmation of payment may be transmitted to the POS.

Abstract: Computer vision systems and methods for end-to end training of neural networks are provided. The system generates a fixed point algorithm for dual-decomposition of a maximum-a-posteriori inference problem and trains the convolutional neural network and a conditional random field with the fixed point algorithm and a plurality of images of a dataset to learn to perform semantic image segmentation. The system can segment an attribute of an image of the dataset by the trained neural network and the conditional random field.

Abstract: A decentralized swarm intelligence algorithm over a network of paired ATMs to prevent or control surface attacks on ATMs. The ATMs may be seeded with an initial swarm intelligence model to identify suspicious activity. An ATM may relay alerts about suspicious activity at that ATM to other paired ATMs. The ATMs use machine learning to update the model and perform swarm intelligence autonomously at the paired ATMs. A bank may provide the initial swarm intelligence model, receive alerts about and analyze the attacks, and provide updated swarm intelligence models to prevent or limit future attacks. Smart contracts may be used to specify rules for performing swarm intelligence using the paired ATMs. Records regarding swarm intelligence models, attempted suspicious attacks including payment instruments that may have been used, actions taken in response to the attacks, and smart contracts may be recorded on a blockchain distributed ledger.

Abstract: An ATM includes a long range WAN module that provides the ATM with a low power WAN (LPWAN) capability for increased resiliency. The ATM and bank application servers generally communicate over an ATM communications network to allow customers to perform banking transactions. When this connection is not functioning, the ATM may continue to be used to perform banking transactions, without interruption, by communicating over a LoRaWAN network with another nearby LPWAN-enabled ATM that is in communication with the bank application servers. The LoRaWAN network may also be used to automatically obtain software to fix an error at the ATM when the software is obtainable via a nearby LPWAN-enabled ATM. The LoRaWAN module may be further used to record a state of operations at the ATM and to use the record to resume the transaction where the transaction was interrupted while in progress due to an ATM outage.

Abstract: Computer vision systems and methods for object detection with reinforcement learning are provided. The system includes a reinforcement learning agent configured to detect an object pertaining to a target object class and a plurality of objects pertaining to different target object classes, such that the reinforcement learning agent determines a bounding box for each of the detected of objects. The system first sets parameters of the reinforcement learning agent. The system then detects an object and/or objects in an image based on the set parameters. Finally, the system determines a bounding box and/or bounding boxes for each of the detected objects.

Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: Bias supplies and plasma processing systems are disclosed. One bias supply comprises an output node, a return node, and a switch network and at least one power supply coupled to the output node and the return node. The switch network and the at least one power supply configured, in combination, to apply an asymmetric periodic voltage waveform and provide a corresponding current waveform at the output node relative to the return node. A timing parameter estimator receives a digital representation of a full cycle of the voltage and current waveforms, and generates a pulse width control signal based on a crossing time that the current waveform crosses a threshold current value after falling from a positive peak current value to control the switch network.

Abstract: An apparatus comprises a memory communicatively coupled to a processor. The memory may be configured to store data exchange requests. The processor may be configured to determine that a data exchange request of the data exchange requests comprises a status indicating that the data exchange request is incomplete, generate a priority value for the data exchange request indicating a batch priority associated with the data exchange request, and assign a weight for the data exchange request indicating that the data exchange request is expected to be completed in one or more batch orders. Further, the processor is configured to generate a batch order comprising a position in a queue corresponding to the batch priority and complete the data exchange request in the decentralized network in accordance with the position in the batch order.

Abstract: Bias supplies and plasma processing systems are disclosed. One bias supply comprises an output node, a return node, and a power section coupled to the output node and the return node. A resonant switch section is coupled to the power section at a first node, a second node, and a third node wherein the resonant switch section is configured to connect and disconnect a current pathway between the first node and the second node to apply an asymmetric periodic voltage waveform at the output node relative to the return node. The asymmetric periodic voltage waveform includes a first portion that begins with a first negative voltage and changes to a positive peak voltage, a second portion that changes from the positive peak voltage level to a third voltage level and a fourth portion that includes a negative voltage ramp from the third voltage level to a fourth voltage level.

Abstract: Bias supplies and plasma processing systems are disclosed. One bias supply comprises an output node, a return node, and a power section coupled to the output node and the return node. A resonant switch section is coupled to the power section at a first node, a second node, and a third node wherein the resonant switch section is configured to connect and disconnect a current pathway between the first node and the second node to apply an asymmetric periodic voltage waveform at the output node relative to the return node. The asymmetric periodic voltage waveform includes a first portion that begins with a first negative voltage and changes to a positive peak voltage, a second portion that changes from the positive peak voltage level to a third voltage level and a fourth portion that includes a negative voltage ramp from the third voltage level to a fourth voltage level.

Abstract: Computer vision systems and methods for automatic parcel alignment are provided. The system receives a geotagged aerial image, parcel information, and semantic information where each of the parcel and semantic information are overlaid on the geotagged aerial image. The system cleans the parcel information and the semantic information. The system optimizes the parcel information by grouping geo-registered parcels present in the geotagged aerial image into a plurality of islands and generating a plurality of parcel alignment solutions for each island of the plurality of islands. The system refines the plurality of parcel alignment solutions for each island and regularizes each island. The system generates a composite parcel alignment solution based on the refined plurality of parcel alignment solutions for each regularized island to align the geo-registered parcels of each regularized island with the geotagged aerial image.

Abstract: Computer vision systems and methods for noisy contour alignment are provided. The system generates a loss function and trains a convolutional neural network with the loss function and a plurality of images of a dataset to learn to align contours with progressively increasing complex forward and backward transforms over increasing scales. The system can align an attribute of an image of the dataset by the trained neural network.

Abstract: Computer vision systems and methods for text classification are provided. The system detects a plurality of text regions in an image and generates a bounding box for each detected text region. The system utilizes a neural network to recognize text present within each bounding box and classifies the recognized text, based on at least one extracted feature of each bounding box and the recognized text present within each bounding box, according to a plurality of predefined tags. The system can associate a key with a value and return a key-value pair for each predefined tag.

Abstract: Computer vision systems and methods for automatic parcel alignment are provided. The system receives a geotagged aerial image, parcel information, and semantic information where each of the parcel and semantic information are overlaid on the geotagged aerial image. The system cleans the parcel information and the semantic information. The system optimizes the parcel information by grouping geo-registered parcels present in the geotagged aerial image into a plurality of islands and generating a plurality of parcel alignment solutions for each island of the plurality of islands. The system refines the plurality of parcel alignment solutions for each island and regularizes each island. The system generates a composite parcel alignment solution based on the refined plurality of parcel alignment solutions for each regularized island to align the geo-registered parcels of each regularized island with the geotagged aerial image.

Abstract: The present invention relates to an improved process for the preparation of a compound of Formula (1), The invention also provides improved processes for the preparation of intermediates used in the synthesis of Formula (1). The compound of Formula (1) is used in the synthesis of Semaglutide.

Abstract: Bias supplies and plasma processing systems are disclosed. One bias supply comprises an output node, a return node, and a power section coupled to the output node and the return node. A resonant switch section is coupled to the power section at a first node, a second node, and a third node wherein the resonant switch section is configured to connect and disconnect a current pathway between the first node and the second node to apply an asymmetric periodic voltage waveform at the output node relative to the return node. The asymmetric periodic voltage waveform includes a first portion that begins with a first negative voltage and changes to a positive peak voltage, a second portion that changes from the positive peak voltage level to a third voltage level and a fourth portion that includes a negative voltage ramp from the third voltage level to a fourth voltage level.